101 Jean-François Ethier Yu Lin OBCS stands for the Ontology of Biological and Clinical Statistics. OBCS is an ontology in the domain of biological and clinical statistics. It is aligned with the Basic Formal Ontology (BFO) and the Ontology for Biomedical Investigations (OBI). OBCS imports all possible biostatistics terms in OBI and includes many additional biostatistics terms, some of which were proposed and discussed in the OBI face-to-face workshop in Ann Arbor in 2012. Barry Smith Marcy Harris Yongqun "Oliver" He Qingzhi Liu Huan Li Jie Zheng Adrien Barton BFO OWL specification label Relates an entity in the ontology to the name of the variable that is used to represent it in the code that generates the BFO OWL file from the lispy specification. Really of interest to developers only BFO OWL specification label BFO CLIF specification label Relates an entity in the ontology to the term that is used to represent it in the the CLIF specification of BFO2 Person:Alan Ruttenberg Really of interest to developers only BFO CLIF specification label editor preferred label The concise, meaningful, and human-friendly name for a class or property preferred by the ontology developers. (US-English) PERSON:Daniel Schober GROUP:OBI:<http://purl.obolibrary.org/obo/obi> editor preferred label editor preferred term editor preferred term example of usage A phrase describing how a class name should be used. May also include other kinds of examples that facilitate immediate understanding of a class semantics, such as widely known prototypical subclasses or instances of the class. Although essential for high level terms, examples for low level terms (e.g., Affymetrix HU133 array) are not PERSON:Daniel Schober GROUP:OBI:<http://purl.obolibrary.org/obo/obi> example of usage has curation status PERSON:Alan Ruttenberg PERSON:Bill Bug PERSON:Melanie Courtot OBI_0000281 has curation status definition The official OBI definition, explaining the meaning of a class or property. Shall be Aristotelian, formalized and normalized. Can be augmented with colloquial definitions. The official definition, explaining the meaning of a class or property. Shall be Aristotelian, formalized and normalized. Can be augmented with colloquial definitions. 2012-04-05: Barry Smith The official OBI definition, explaining the meaning of a class or property: 'Shall be Aristotelian, formalized and normalized. Can be augmented with colloquial definitions' is terrible. Can you fix to something like: A statement of necessary and sufficient conditions explaining the meaning of an expression referring to a class or property. Alan Ruttenberg Your proposed definition is a reasonable candidate, except that it is very common that necessary and sufficient conditions are not given. Mostly they are necessary, occasionally they are necessary and sufficient or just sufficient. Often they use terms that are not themselves defined and so they effectively can't be evaluated by those criteria. On the specifics of the proposed definition: We don't have definitions of 'meaning' or 'expression' or 'property'. For 'reference' in the intended sense I think we use the term 'denotation'. For 'expression', I think we you mean symbol, or identifier. For 'meaning' it differs for class and property. For class we want documentation that let's the intended reader determine whether an entity is instance of the class, or not. For property we want documentation that let's the intended reader determine, given a pair of potential relata, whether the assertion that the relation holds is true. The 'intended reader' part suggests that we also specify who, we expect, would be able to understand the definition, and also generalizes over human and computer reader to include textual and logical definition. Personally, I am more comfortable weakening definition to documentation, with instructions as to what is desirable. We also have the outstanding issue of how to aim different definitions to different audiences. A clinical audience reading chebi wants a different sort of definition documentation/definition from a chemistry trained audience, and similarly there is a need for a definition that is adequate for an ontologist to work with. PERSON:Daniel Schober GROUP:OBI:<http://purl.obolibrary.org/obo/obi> definition definition definition textual definition editor note An administrative note intended for its editor. It may not be included in the publication version of the ontology, so it should contain nothing necessary for end users to understand the ontology. PERSON:Daniel Schober GROUP:OBI:<http://purl.obfoundry.org/obo/obi> editor note term editor Name of editor entering the term in the file. The term editor is a point of contact for information regarding the term. The term editor may be, but is not always, the author of the definition, which may have been worked upon by several people 20110707, MC: label update to term editor and definition modified accordingly. See http://code.google.com/p/information-artifact-ontology/issues/detail?id=115. PERSON:Daniel Schober GROUP:OBI:<http://purl.obolibrary.org/obo/obi> term editor alternative term An alternative name for a class or property which means the same thing as the preferred name (semantically equivalent) PERSON:Daniel Schober GROUP:OBI:<http://purl.obolibrary.org/obo/obi> alternative term definition source formal citation, e.g. identifier in external database to indicate / attribute source(s) for the definition. Free text indicate / attribute source(s) for the definition. EXAMPLE: Author Name, URI, MeSH Term C04, PUBMED ID, Wiki uri on 31.01.2007 PERSON:Daniel Schober Discussion on obo-discuss mailing-list, see http://bit.ly/hgm99w GROUP:OBI:<http://purl.obolibrary.org/obo/obi> definition source curator note An administrative note of use for a curator but of no use for a user PERSON:Alan Ruttenberg curator note imported from For external terms/classes, the ontology from which the term was imported PERSON:Alan Ruttenberg PERSON:Melanie Courtot GROUP:OBI:<http://purl.obolibrary.org/obo/obi> imported from elucidation person:Alan Ruttenberg Person:Barry Smith Primitive terms in a highest-level ontology such as BFO are terms which are so basic to our understanding of reality that there is no way of defining them in a non-circular fashion. For these, therefore, we can provide only elucidations, supplemented by examples and by axioms elucidation has associated axiom(nl) Person:Alan Ruttenberg Person:Alan Ruttenberg An axiom associated with a term expressed using natural language has associated axiom(nl) has associated axiom(fol) Person:Alan Ruttenberg Person:Alan Ruttenberg An axiom expressed in first order logic using CLIF syntax has associated axiom(fol) A normal distribution probability density function has a formula of: f(x) = 1/(√(2 π) σ) e^-((x - μ)^2/(2 σ^2)) an annotation property that represents a mathematical formula. Asiyah Yu Lin, Jie Zheng, Yongqun He mathematical formula ISA alternative term An alternative term used by the ISA tools project (http://isa-tools.org). Requested by Alejandra Gonzalez-Beltran https://sourceforge.net/tracker/?func=detail&aid=3603413&group_id=177891&atid=886178 Person: Alejandra Gonzalez-Beltran Person: Philippe Rocca-Serra ISA tools project (http://isa-tools.org) ISA alternative term NIAID GSCID-BRC alternative term An alternative term used by the National Institute of Allergy and Infectious Diseases (NIAID) Genomic Sequencing Centers for Infectious Diseases (GSCID) and Bioinformatics Resource Centers (BRC). PERSON: Chris Stoeckert, Jie Zheng NIAID GSCID-BRC metadata working group NIAID GSCID-BRC alternative term IEDB alternative term An alternative term used by the IEDB. PERSON:Randi Vita, Jason Greenbaum, Bjoern Peters IEDB IEDB alternative term temporal interpretation temporal interpretation https://code.google.com/p/obo-relations/wiki/ROAndTime Description may include but is not limited to: an abstract, table of contents, reference to a graphical representation of content or a free-text account of the content. An account of the content of the resource. Description Description The present resource may be derived from the Source resource in whole or in part. Recommended best practice is to reference the resource by means of a string or number conforming to a formal identification system. A reference to a resource from which the present resource is derived. Source Source database_cross_reference label part of my brain is part of my body (continuant parthood, two material entities) my stomach cavity is part of my stomach (continuant parthood, immaterial entity is part of material entity) this day is part of this year (occurrent parthood) a core relation that holds between a part and its whole Everything is part of itself. Any part of any part of a thing is itself part of that thing. Two distinct things cannot be part of each other. Occurrents are not subject to change and so parthood between occurrents holds for all the times that the part exists. Many continuants are subject to change, so parthood between continuants will only hold at certain times, but this is difficult to specify in OWL. See https://code.google.com/p/obo-relations/wiki/ROAndTime Parthood requires the part and the whole to have compatible classes: only an occurrent can be part of an occurrent; only a process can be part of a process; only a continuant can be part of a continuant; only an independent continuant can be part of an independent continuant; only an immaterial entity can be part of an immaterial entity; only a specifically dependent continuant can be part of a specifically dependent continuant; only a generically dependent continuant can be part of a generically dependent continuant. (This list is not exhaustive.) A continuant cannot be part of an occurrent: use 'participates in'. An occurrent cannot be part of a continuant: use 'has participant'. A material entity cannot be part of an immaterial entity: use 'has location'. A specifically dependent continuant cannot be part of an independent continuant: use 'inheres in'. An independent continuant cannot be part of a specifically dependent continuant: use 'bearer of'. part_of part of http://www.obofoundry.org/ro/#OBO_REL:part_of has part my body has part my brain (continuant parthood, two material entities) my stomach has part my stomach cavity (continuant parthood, material entity has part immaterial entity) this year has part this day (occurrent parthood) a core relation that holds between a whole and its part Everything has itself as a part. Any part of any part of a thing is itself part of that thing. Two distinct things cannot have each other as a part. Occurrents are not subject to change and so parthood between occurrents holds for all the times that the part exists. Many continuants are subject to change, so parthood between continuants will only hold at certain times, but this is difficult to specify in OWL. See https://code.google.com/p/obo-relations/wiki/ROAndTime Parthood requires the part and the whole to have compatible classes: only an occurrent have an occurrent as part; only a process can have a process as part; only a continuant can have a continuant as part; only an independent continuant can have an independent continuant as part; only a specifically dependent continuant can have a specifically dependent continuant as part; only a generically dependent continuant can have a generically dependent continuant as part. (This list is not exhaustive.) A continuant cannot have an occurrent as part: use 'participates in'. An occurrent cannot have a continuant as part: use 'has participant'. An immaterial entity cannot have a material entity as part: use 'location of'. An independent continuant cannot have a specifically dependent continuant as part: use 'bearer of'. A specifically dependent continuant cannot have an independent continuant as part: use 'inheres in'. has_part has part realized in this disease is realized in this disease course this fragility is realized in this shattering this investigator role is realized in this investigation is realized by realized_in [copied from inverse property 'realizes'] to say that b realizes c at t is to assert that there is some material entity d & b is a process which has participant d at t & c is a disposition or role of which d is bearer_of at t& the type instantiated by b is correlated with the type instantiated by c. (axiom label in BFO2 Reference: [059-003]) Paraphrase of elucidation: a relation between a realizable entity and a process, where there is some material entity that is bearer of the realizable entity and participates in the process, and the realizable entity comes to be realized in the course of the process realized in realizes this disease course realizes this disease this investigation realizes this investigator role this shattering realizes this fragility to say that b realizes c at t is to assert that there is some material entity d & b is a process which has participant d at t & c is a disposition or role of which d is bearer_of at t& the type instantiated by b is correlated with the type instantiated by c. (axiom label in BFO2 Reference: [059-003]) Paraphrase of elucidation: a relation between a process and a realizable entity, where there is some material entity that is bearer of the realizable entity and participates in the process, and the realizable entity comes to be realized in the course of the process realizes preceded by An example is: translation preceded_by transcription; aging preceded_by development (not however death preceded_by aging). Where derives_from links classes of continuants, preceded_by links classes of processes. Clearly, however, these two relations are not independent of each other. Thus if cells of type C1 derive_from cells of type C, then any cell division involving an instance of C1 in a given lineage is preceded_by cellular processes involving an instance of C. The assertion P preceded_by P1 tells us something about Ps in general: that is, it tells us something about what happened earlier, given what we know about what happened later. Thus it does not provide information pointing in the opposite direction, concerning instances of P1 in general; that is, that each is such as to be succeeded by some instance of P. Note that an assertion to the effect that P preceded_by P1 is rather weak; it tells us little about the relations between the underlying instances in virtue of which the preceded_by relation obtains. Typically we will be interested in stronger relations, for example in the relation immediately_preceded_by, or in relations which combine preceded_by with a condition to the effect that the corresponding instances of P and P1 share participants, or that their participants are connected by relations of derivation, or (as a first step along the road to a treatment of causality) that the one process in some way affects (for example, initiates or regulates) the other. is preceded by preceded_by http://www.obofoundry.org/ro/#OBO_REL:preceded_by preceded by precedes precedes has measurement unit label has measurement unit label is about This document is about information artifacts and their representations is_about is a (currently) primitive relation that relates an information artifact to an entity. 7/6/2009 Alan Ruttenberg. Following discussion with Jonathan Rees, and introduction of "mentions" relation. Weaken the is_about relationship to be primitive. We will try to build it back up by elaborating the various subproperties that are more precisely defined. Some currently missing phenomena that should be considered "about" are predications - "The only person who knows the answer is sitting beside me" , Allegory, Satire, and other literary forms that can be topical without explicitly mentioning the topic. person:Alan Ruttenberg Smith, Ceusters, Ruttenberg, 2000 years of philosophy is about denotes A person's name denotes the person. A variable name in a computer program denotes some piece of memory. Lexically equivalent strings can denote different things, for instance "Alan" can denote different people. In each case of use, there is a case of the denotation relation obtaining, between "Alan" and the person that is being named. denotes is a primitive, instance-level, relation obtaining between an information content entity and some portion of reality. Denotation is what happens when someone creates an information content entity E in order to specifically refer to something. The only relation between E and the thing is that E can be used to 'pick out' the thing. This relation connects those two together. Freedictionary.com sense 3: To signify directly; refer to specifically 2009-11-10 Alan Ruttenberg. Old definition said the following to emphasize the generic nature of this relation. We no longer have 'specifically denotes', which would have been primitive, so make this relation primitive. g denotes r =def r is a portion of reality there is some c that is a concretization of g every c that is a concretization of g specifically denotes r person:Alan Ruttenberg Conversations with Barry Smith, Werner Ceusters, Bjoern Peters, Michel Dumontier, Melanie Courtot, James Malone, Bill Hogan denotes is quality measurement of m is a quality measurement of q at t when q is a quality there is a measurement process p that has specified output m, a measurement datum, that is about q 8/6/2009 Alan Ruttenberg: The strategy is to be rather specific with this relationship. There are other kinds of measurements that are not of qualities, such as those that measure time. We will add these as separate properties for the moment and see about generalizing later From the second IAO workshop [Alan Ruttenberg 8/6/2009: not completely current, though bringing in comparison is probably important] This one is the one we are struggling with at the moment. The issue is what a measurement measures. On the one hand saying that it measures the quality would include it "measuring" the bearer = referring to the bearer in the measurement. However this makes comparisons of two different things not possible. On the other hand not having it inhere in the bearer, on the face of it, breaks the audit trail. Werner suggests a solution based on "Magnitudes" a proposal for which we are awaiting details. -- From the second IAO workshop, various comments, [commented on by Alan Ruttenberg 8/6/2009] unit of measure is a quality, e.g. the length of a ruler. [We decided to hedge on what units of measure are, instead talking about measurement unit labels, which are the information content entities that are about whatever measurement units are. For IAO we need that information entity in any case. See the term measurement unit label] [Some struggling with the various subflavors of is_about. We subsequently removed the relation represents, and describes until and only when we have a better theory] a represents b means either a denotes b or a describes describe: a describes b means a is about b and a allows an inference of at least one quality of b We have had a long discussion about denotes versus describes. From the second IAO workshop: An attempt at tieing the quality to the measurement datum more carefully. a is a magnitude means a is a determinate quality particular inhering in some bearer b existing at a time t that can be represented/denoted by an information content entity e that has parts denoting a unit of measure, a number, and b. The unit of measure is an instance of the determinable quality. From the second meeting on IAO: An attempt at defining assay using Barry's "reliability" wording assay: process and has_input some material entity and has_output some information content entity and which is such that instances of this process type reliably generate outputs that describes the input. This one is the one we are struggling with at the moment. The issue is what a measurement measures. On the one hand saying that it measures the quality would include it "measuring" the bearer = referring to the bearer in the measurement. However this makes comparisons of two different things not possible. On the other hand not having it inhere in the bearer, on the face of it, breaks the audit trail. Werner suggests a solution based on "Magnitudes" a proposal for which we are awaiting details. Alan Ruttenberg is quality measurement of has coordinate unit label relating a cartesian spatial coordinate datum to a unit label that together with the values represent a point has coordinate unit label is duration of relates a process to a time-measurement-datum that represents the duration of the process Person:Alan Ruttenberg is duration of has time stamp relates a time stamped measurement datum to the time measurement datum that denotes the time when the measurement was taken Alan Ruttenberg has time stamp has measurement datum relates a time stamped measurement datum to the measurement datum that was measured Alan Ruttenberg has measurement datum a relation between a data set and a probability distribution Yongqun He, Jie Zheng, Asiyah Yu Lin has probability distribution a relation between a probability distribution and probability. Yongqun He, Jie Zheng, Asiyah Yu Lin has probability density function A student t-test follows the probability distribution of a student distribution. An object property that represents a relation between a statistical test and a probability distribution. Yongqun He, Qingzhi Liu test follows probability distribution is_supported_by_data The relation between the conclusion "Gene tpbA is involved in EPS production" and the data items produced using two sets of organisms, one being a tpbA knockout, the other being tpbA wildtype tested in polysacharide production assays and analyzed using an ANOVA. The relation between a data item and a conclusion where the conclusion is the output of a data interpreting process and the data item is used as an input to that process OBI OBI Philly 2011 workshop is_supported_by_data has_specified_input see is_input_of example_of_usage A relation between a planned process and a continuant participating in that process that is not created during the process. The presence of the continuant during the process is explicitly specified in the plan specification which the process realizes the concretization of. 8/17/09: specified inputs of one process are not necessarily specified inputs of a larger process that it is part of. This is in contrast to how 'has participant' works. PERSON: Alan Ruttenberg PERSON: Bjoern Peters PERSON: Larry Hunter PERSON: Melanie Coutot has_specified_input is_specified_input_of some Autologous EBV(Epstein-Barr virus)-transformed B-LCL (B lymphocyte cell line) is_input_for instance of Chromum Release Assay described at https://wiki.cbil.upenn.edu/obiwiki/index.php/Chromium_Release_assay A relation between a planned process and a continuant participating in that process that is not created during the process. The presence of the continuant during the process is explicitly specified in the plan specification which the process realizes the concretization of. Alan Ruttenberg PERSON:Bjoern Peters is_specified_input_of has_specified_output A relation between a planned process and a continuant participating in that process. The presence of the continuant at the end of the process is explicitly specified in the objective specification which the process realizes the concretization of. PERSON: Alan Ruttenberg PERSON: Bjoern Peters PERSON: Larry Hunter PERSON: Melanie Courtot has_specified_output is_specified_output_of A relation between a planned process and a continuant participating in that process. The presence of the continuant at the end of the process is explicitly specified in the objective specification which the process realizes the concretization of. Alan Ruttenberg PERSON:Bjoern Peters is_specified_output_of achieves_planned_objective A cell sorting process achieves the objective specification 'material separation objective' This relation obtains between a planned process and a objective specification when the criteria specified in the objective specification are met at the end of the planned process. BP, AR, PPPB branch PPPB branch derived modified according to email thread from 1/23/09 in accordince with DT and PPPB branch achieves_planned_objective has grain the relation of the cells in the finger of the skin to the finger, in which an indeterminate number of grains are parts of the whole by virtue of being grains in a collective that is part of the whole, and in which removing one granular part does not nec- essarily damage or diminish the whole. Ontological Whether there is a fixed, or nearly fixed number of parts - e.g. fingers of the hand, chambers of the heart, or wheels of a car - such that there can be a notion of a single one being missing, or whether, by contrast, the number of parts is indeterminate - e.g., cells in the skin of the hand, red cells in blood, or rubber molecules in the tread of the tire of the wheel of the car. Discussion in Karslruhe with, among others, Alan Rector, Stefan Schulz, Marijke Keet, Melanie Courtot, and Alan Ruttenberg. Definition take from the definition of granular parthood in the cited paper. Needs work to put into standard form PERSON: Alan Ruttenberg PAPER: Granularity, scale and collectivity: When size does and does not matter, Alan Rector, Jeremy Rogers, Thomas Bittner, Journal of Biomedical Informatics 39 (2006) 333-349 has grain has category label A relation between a categorical measurement data item and the categorical label that indicates the value of that data item on the categorical scale. has category label has value specification A relation between an information content entity and a value specification that specifies its value. PERSON: James A. Overton OBI has value specification inheres in this fragility inheres in this vase this red color inheres in this apple a relation between a specifically dependent continuant (the dependent) and an independent continuant (the bearer), in which the dependent specifically depends on the bearer for its existence A dependent inheres in its bearer at all times for which the dependent exists. inheres_in inheres in bearer of this apple is bearer of this red color this vase is bearer of this fragility a relation between an independent continuant (the bearer) and a specifically dependent continuant (the dependent), in which the dependent specifically depends on the bearer for its existence A bearer can have many dependents, and its dependents can exist for different periods of time, but none of its dependents can exist when the bearer does not exist. bearer_of is bearer of bearer of participates in this blood clot participates in this blood coagulation this input material (or this output material) participates in this process this investigator participates in this investigation a relation between a continuant and a process, in which the continuant is somehow involved in the process participates_in participates in has participant this blood coagulation has participant this blood clot this investigation has participant this investigator this process has participant this input material (or this output material) a relation between a process and a continuant, in which the continuant is somehow involved in the process Has_participant is a primitive instance-level relation between a process, a continuant, and a time at which the continuant participates in some way in the process. The relation obtains, for example, when this particular process of oxygen exchange across this particular alveolar membrane has_participant this particular sample of hemoglobin at this particular time. has_participant http://www.obofoundry.org/ro/#OBO_REL:has_participant has participant is concretized as A journal article is an information artifact that inheres in some number of printed journals. For each copy of the printed journal there is some quality that carries the journal article, such as a pattern of ink. The journal article (a generically dependent continuant) is concretized as the quality (a specifically dependent continuant), and both depend on that copy of the printed journal (an independent continuant). An investigator reads a protocol and forms a plan to carry out an assay. The plan is a realizable entity (a specifically dependent continuant) that concretizes the protocol (a generically dependent continuant), and both depend on the investigator (an independent continuant). The plan is then realized by the assay (a process). A relationship between a generically dependent continuant and a specifically dependent continuant, in which the generically dependent continuant depends on some independent continuant in virtue of the fact that the specifically dependent continuant also depends on that same independent continuant. A generically dependent continuant may be concretized as multiple specifically dependent continuants. is concretized as concretizes A journal article is an information artifact that inheres in some number of printed journals. For each copy of the printed journal there is some quality that carries the journal article, such as a pattern of ink. The quality (a specifically dependent continuant) concretizes the journal article (a generically dependent continuant), and both depend on that copy of the printed journal (an independent continuant). An investigator reads a protocol and forms a plan to carry out an assay. The plan is a realizable entity (a specifically dependent continuant) that concretizes the protocol (a generically dependent continuant), and both depend on the investigator (an independent continuant). The plan is then realized by the assay (a process). A relationship between a specifically dependent continuant and a generically dependent continuant, in which the generically dependent continuant depends on some independent continuant in virtue of the fact that the specifically dependent continuant also depends on that same independent continuant. Multiple specifically dependent continuants can concretize the same generically dependent continuant. concretizes function of this catalysis function is a function of this enzyme a relation between a function and an independent continuant (the bearer), in which the function specifically depends on the bearer for its existence A function inheres in its bearer at all times for which the function exists, however the function need not be realized at all the times that the function exists. function_of is function of function of role of this investigator role is a role of this person a relation between a role and an independent continuant (the bearer), in which the role specifically depends on the bearer for its existence A role inheres in its bearer at all times for which the role exists, however the role need not be realized at all the times that the role exists. is role of role_of role of has function this enzyme has function this catalysis function (more colloquially: this enzyme has this catalysis function) a relation between an independent continuant (the bearer) and a function, in which the function specifically depends on the bearer for its existence A bearer can have many functions, and its functions can exist for different periods of time, but none of its functions can exist when the bearer does not exist. A function need not be realized at all the times that the function exists. has_function has function has role this person has role this investigator role (more colloquially: this person has this role of investigator) a relation between an independent continuant (the bearer) and a role, in which the role specifically depends on the bearer for its existence A bearer can have many roles, and its roles can exist for different periods of time, but none of its roles can exist when the bearer does not exist. A role need not be realized at all the times that the role exists. has_role has role location of my head is the location of my brain this cage is the location of this rat a relation between two independent continuants, the location and the target, in which the target is entirely within the location Most location relations will only hold at certain times, but this is difficult to specify in OWL. See https://code.google.com/p/obo-relations/wiki/ROAndTime location_of location of located in my brain is located in my head this rat is located in this cage a relation between two independent continuants, the target and the location, in which the target is entirely within the location Location as a relation between instances: The primitive instance-level relation c located_in r at t reflects the fact that each continuant is at any given time associated with exactly one spatial region, namely its exact location. Following we can use this relation to define a further instance-level location relation - not between a continuant and the region which it exactly occupies, but rather between one continuant and another. c is located in c1, in this sense, whenever the spatial region occupied by c is part_of the spatial region occupied by c1. Note that this relation comprehends both the relation of exact location between one continuant and another which obtains when r and r1 are identical (for example, when a portion of fluid exactly fills a cavity), as well as those sorts of inexact location relations which obtain, for example, between brain and head or between ovum and uterus Most location relations will only hold at certain times, but this is difficult to specify in OWL. See https://code.google.com/p/obo-relations/wiki/ROAndTime located_in http://www.obofoundry.org/ro/#OBO_REL:located_in located in immediately preceded by David Osumi-Sutherland starts_at_end_of X immediately_preceded_by Y iff: end(X) simultaneous_with start(Y) immediately preceded by immediately precedes David Osumi-Sutherland ends_at_start_of meets X immediately_precedes_Y iff: end(X) simultaneous_with start(Y) immediately precedes temporal relation move to BFO? Allen A relation that holds between two occurrents. This is a grouping relation that collects together all the Allen relations. temporal relation starts inverse of starts with Chris Mungall Allen starts has member is a mereological relation between a collection and an item. has member has measurement value has measurement value has x coordinate value has x coordinate value has z coordinate value has z coordinate value has y coordinate value has y coordinate value has_feature_value has_feature_value datatype property is used to describe the feature values which the feature class can contain, for example has_base can have feature values of nonNegativeInteger values. James Malone has_feature_value has specified value A relation between a value specification and a number that quantifies it. A range of 'real' might be better than 'float'. For now we follow 'has measurement value' until we can consider technical issues with SPARQL queries and reasoning. PERSON: James A. Overton OBI has specified value entity Entity entity Julius Caesar Verdi’s Requiem the Second World War your body mass index BFO 2 Reference: In all areas of empirical inquiry we encounter general terms of two sorts. First are general terms which refer to universals or types:animaltuberculosissurgical procedurediseaseSecond, are general terms used to refer to groups of entities which instantiate a given universal but do not correspond to the extension of any subuniversal of that universal because there is nothing intrinsic to the entities in question by virtue of which they – and only they – are counted as belonging to the given group. Examples are: animal purchased by the Emperortuberculosis diagnosed on a Wednesdaysurgical procedure performed on a patient from Stockholmperson identified as candidate for clinical trial #2056-555person who is signatory of Form 656-PPVpainting by Leonardo da VinciSuch terms, which represent what are called ‘specializations’ in [81 Entity doesn't have a closure axiom because the subclasses don't necessarily exhaust all possibilites. For example Werner Ceusters 'portions of reality' include 4 sorts, entities (as BFO construes them), universals, configurations, and relations. It is an open question as to whether entities as construed in BFO will at some point also include these other portions of reality. See, for example, 'How to track absolutely everything' at http://www.referent-tracking.com/_RTU/papers/CeustersICbookRevised.pdf An entity is anything that exists or has existed or will exist. (axiom label in BFO2 Reference: [001-001]) entity continuant Continuant continuant An entity that exists in full at any time in which it exists at all, persists through time while maintaining its identity and has no temporal parts. BFO 2 Reference: Continuant entities are entities which can be sliced to yield parts only along the spatial dimension, yielding for example the parts of your table which we call its legs, its top, its nails. ‘My desk stretches from the window to the door. It has spatial parts, and can be sliced (in space) in two. With respect to time, however, a thing is a continuant.’ [60, p. 240 Continuant doesn't have a closure axiom because the subclasses don't necessarily exhaust all possibilites. For example, in an expansion involving bringing in some of Ceuster's other portions of reality, questions are raised as to whether universals are continuants A continuant is an entity that persists, endures, or continues to exist through time while maintaining its identity. (axiom label in BFO2 Reference: [008-002]) if b is a continuant and if, for some t, c has_continuant_part b at t, then c is a continuant. (axiom label in BFO2 Reference: [126-001]) if b is a continuant and if, for some t, cis continuant_part of b at t, then c is a continuant. (axiom label in BFO2 Reference: [009-002]) if b is a material entity, then there is some temporal interval (referred to below as a one-dimensional temporal region) during which b exists. (axiom label in BFO2 Reference: [011-002]) (forall (x y) (if (and (Continuant x) (exists (t) (continuantPartOfAt y x t))) (Continuant y))) // axiom label in BFO2 CLIF: [009-002] (forall (x y) (if (and (Continuant x) (exists (t) (hasContinuantPartOfAt y x t))) (Continuant y))) // axiom label in BFO2 CLIF: [126-001] (forall (x) (if (Continuant x) (Entity x))) // axiom label in BFO2 CLIF: [008-002] (forall (x) (if (Material Entity x) (exists (t) (and (TemporalRegion t) (existsAt x t))))) // axiom label in BFO2 CLIF: [011-002] continuant occurrent Occurrent occurrent An entity that has temporal parts and that happens, unfolds or develops through time. BFO 2 Reference: every occurrent that is not a temporal or spatiotemporal region is s-dependent on some independent continuant that is not a spatial region BFO 2 Reference: s-dependence obtains between every process and its participants in the sense that, as a matter of necessity, this process could not have existed unless these or those participants existed also. A process may have a succession of participants at different phases of its unfolding. Thus there may be different players on the field at different times during the course of a football game; but the process which is the entire game s-depends_on all of these players nonetheless. Some temporal parts of this process will s-depend_on on only some of the players. Occurrent doesn't have a closure axiom because the subclasses don't necessarily exhaust all possibilites. An example would be the sum of a process and the process boundary of another process. Simons uses different terminology for relations of occurrents to regions: Denote the spatio-temporal location of a given occurrent e by 'spn[e]' and call this region its span. We may say an occurrent is at its span, in any larger region, and covers any smaller region. Now suppose we have fixed a frame of reference so that we can speak not merely of spatio-temporal but also of spatial regions (places) and temporal regions (times). The spread of an occurrent, (relative to a frame of reference) is the space it exactly occupies, and its spell is likewise the time it exactly occupies. We write 'spr[e]' and `spl[e]' respectively for the spread and spell of e, omitting mention of the frame. An occurrent is an entity that unfolds itself in time or it is the instantaneous boundary of such an entity (for example a beginning or an ending) or it is a temporal or spatiotemporal region which such an entity occupies_temporal_region or occupies_spatiotemporal_region. (axiom label in BFO2 Reference: [077-002]) Every occurrent occupies_spatiotemporal_region some spatiotemporal region. (axiom label in BFO2 Reference: [108-001]) b is an occurrent entity iff b is an entity that has temporal parts. (axiom label in BFO2 Reference: [079-001]) (forall (x) (if (Occurrent x) (exists (r) (and (SpatioTemporalRegion r) (occupiesSpatioTemporalRegion x r))))) // axiom label in BFO2 CLIF: [108-001] (forall (x) (iff (Occurrent x) (and (Entity x) (exists (y) (temporalPartOf y x))))) // axiom label in BFO2 CLIF: [079-001] occurrent ic IndependentContinuant independent continuant a chair a heart a leg a molecule a spatial region an atom an orchestra. an organism the bottom right portion of a human torso the interior of your mouth A continuant that is a bearer of quality and realizable entity entities, in which other entities inhere and which itself cannot inhere in anything. b is an independent continuant = Def. b is a continuant which is such that there is no c and no t such that b s-depends_on c at t. (axiom label in BFO2 Reference: [017-002]) For any independent continuant b and any time t there is some spatial region r such that b is located_in r at t. (axiom label in BFO2 Reference: [134-001]) For every independent continuant b and time t during the region of time spanned by its life, there are entities which s-depends_on b during t. (axiom label in BFO2 Reference: [018-002]) (forall (x t) (if (IndependentContinuant x) (exists (r) (and (SpatialRegion r) (locatedInAt x r t))))) // axiom label in BFO2 CLIF: [134-001] (forall (x t) (if (and (IndependentContinuant x) (existsAt x t)) (exists (y) (and (Entity y) (specificallyDependsOnAt y x t))))) // axiom label in BFO2 CLIF: [018-002] (iff (IndependentContinuant a) (and (Continuant a) (not (exists (b t) (specificallyDependsOnAt a b t))))) // axiom label in BFO2 CLIF: [017-002] independent continuant s-region SpatialRegion spatial region BFO 2 Reference: Spatial regions do not participate in processes. Spatial region doesn't have a closure axiom because the subclasses don't exhaust all possibilites. An example would be the union of a spatial point and a spatial line that doesn't overlap the point, or two spatial lines that intersect at a single point. In both cases the resultant spatial region is neither 0-dimensional, 1-dimensional, 2-dimensional, or 3-dimensional. A spatial region is a continuant entity that is a continuant_part_of spaceR as defined relative to some frame R. (axiom label in BFO2 Reference: [035-001]) All continuant parts of spatial regions are spatial regions. (axiom label in BFO2 Reference: [036-001]) (forall (x y t) (if (and (SpatialRegion x) (continuantPartOfAt y x t)) (SpatialRegion y))) // axiom label in BFO2 CLIF: [036-001] (forall (x) (if (SpatialRegion x) (Continuant x))) // axiom label in BFO2 CLIF: [035-001] spatial region 2d-s-region TwoDimensionalSpatialRegion two-dimensional spatial region an infinitely thin plane in space. the surface of a sphere-shaped part of space A two-dimensional spatial region is a spatial region that is of two dimensions. (axiom label in BFO2 Reference: [039-001]) (forall (x) (if (TwoDimensionalSpatialRegion x) (SpatialRegion x))) // axiom label in BFO2 CLIF: [039-001] two-dimensional spatial region process Process process a process of cell-division, \ a beating of the heart a process of meiosis a process of sleeping the course of a disease the flight of a bird the life of an organism your process of aging. An occurrent that has temporal proper parts and for some time t, p s-depends_on some material entity at t. p is a process = Def. p is an occurrent that has temporal proper parts and for some time t, p s-depends_on some material entity at t. (axiom label in BFO2 Reference: [083-003]) BFO 2 Reference: The realm of occurrents is less pervasively marked by the presence of natural units than is the case in the realm of independent continuants. Thus there is here no counterpart of ‘object’. In BFO 1.0 ‘process’ served as such a counterpart. In BFO 2.0 ‘process’ is, rather, the occurrent counterpart of ‘material entity’. Those natural – as contrasted with engineered, which here means: deliberately executed – units which do exist in the realm of occurrents are typically either parasitic on the existence of natural units on the continuant side, or they are fiat in nature. Thus we can count lives; we can count football games; we can count chemical reactions performed in experiments or in chemical manufacturing. We cannot count the processes taking place, for instance, in an episode of insect mating behavior.Even where natural units are identifiable, for example cycles in a cyclical process such as the beating of a heart or an organism’s sleep/wake cycle, the processes in question form a sequence with no discontinuities (temporal gaps) of the sort that we find for instance where billiard balls or zebrafish or planets are separated by clear spatial gaps. Lives of organisms are process units, but they too unfold in a continuous series from other, prior processes such as fertilization, and they unfold in turn in continuous series of post-life processes such as post-mortem decay. Clear examples of boundaries of processes are almost always of the fiat sort (midnight, a time of death as declared in an operating theater or on a death certificate, the initiation of a state of war) (iff (Process a) (and (Occurrent a) (exists (b) (properTemporalPartOf b a)) (exists (c t) (and (MaterialEntity c) (specificallyDependsOnAt a c t))))) // axiom label in BFO2 CLIF: [083-003] process disposition Disposition disposition an atom of element X has the disposition to decay to an atom of element Y certain people have a predisposition to colon cancer children are innately disposed to categorize objects in certain ways. the cell wall is disposed to filter chemicals in endocytosis and exocytosis BFO 2 Reference: Dispositions exist along a strength continuum. Weaker forms of disposition are realized in only a fraction of triggering cases. These forms occur in a significant number of cases of a similar type. b is a disposition means: b is a realizable entity & b’s bearer is some material entity & b is such that if it ceases to exist, then its bearer is physically changed, & b’s realization occurs when and because this bearer is in some special physical circumstances, & this realization occurs in virtue of the bearer’s physical make-up. (axiom label in BFO2 Reference: [062-002]) If b is a realizable entity then for all t at which b exists, b s-depends_on some material entity at t. (axiom label in BFO2 Reference: [063-002]) (forall (x t) (if (and (RealizableEntity x) (existsAt x t)) (exists (y) (and (MaterialEntity y) (specificallyDepends x y t))))) // axiom label in BFO2 CLIF: [063-002] (forall (x) (if (Disposition x) (and (RealizableEntity x) (exists (y) (and (MaterialEntity y) (bearerOfAt x y t)))))) // axiom label in BFO2 CLIF: [062-002] disposition realizable RealizableEntity realizable entity the disposition of this piece of metal to conduct electricity. the disposition of your blood to coagulate the function of your reproductive organs the role of being a doctor the role of this boundary to delineate where Utah and Colorado meet A specifically dependent continuant that inheres in continuant entities and are not exhibited in full at every time in which it inheres in an entity or group of entities. The exhibition or actualization of a realizable entity is a particular manifestation, functioning or process that occurs under certain circumstances. To say that b is a realizable entity is to say that b is a specifically dependent continuant that inheres in some independent continuant which is not a spatial region and is of a type instances of which are realized in processes of a correlated type. (axiom label in BFO2 Reference: [058-002]) All realizable dependent continuants have independent continuants that are not spatial regions as their bearers. (axiom label in BFO2 Reference: [060-002]) (forall (x t) (if (RealizableEntity x) (exists (y) (and (IndependentContinuant y) (not (SpatialRegion y)) (bearerOfAt y x t))))) // axiom label in BFO2 CLIF: [060-002] (forall (x) (if (RealizableEntity x) (and (SpecificallyDependentContinuant x) (exists (y) (and (IndependentContinuant y) (not (SpatialRegion y)) (inheresIn x y)))))) // axiom label in BFO2 CLIF: [058-002] realizable entity 0d-s-region ZeroDimensionalSpatialRegion zero-dimensional spatial region A zero-dimensional spatial region is a point in space. (axiom label in BFO2 Reference: [037-001]) (forall (x) (if (ZeroDimensionalSpatialRegion x) (SpatialRegion x))) // axiom label in BFO2 CLIF: [037-001] zero-dimensional spatial region quality Quality quality the ambient temperature of this portion of air the color of a tomato the length of the circumference of your waist the mass of this piece of gold. the shape of your nose the shape of your nostril a quality is a specifically dependent continuant that, in contrast to roles and dispositions, does not require any further process in order to be realized. (axiom label in BFO2 Reference: [055-001]) If an entity is a quality at any time that it exists, then it is a quality at every time that it exists. (axiom label in BFO2 Reference: [105-001]) (forall (x) (if (Quality x) (SpecificallyDependentContinuant x))) // axiom label in BFO2 CLIF: [055-001] (forall (x) (if (exists (t) (and (existsAt x t) (Quality x))) (forall (t_1) (if (existsAt x t_1) (Quality x))))) // axiom label in BFO2 CLIF: [105-001] quality sdc SpecificallyDependentContinuant specifically dependent continuant Reciprocal specifically dependent continuants: the function of this key to open this lock and the mutually dependent disposition of this lock: to be opened by this key of one-sided specifically dependent continuants: the mass of this tomato of relational dependent continuants (multiple bearers): John’s love for Mary, the ownership relation between John and this statue, the relation of authority between John and his subordinates. the disposition of this fish to decay the function of this heart: to pump blood the mutual dependence of proton donors and acceptors in chemical reactions [79 the mutual dependence of the role predator and the role prey as played by two organisms in a given interaction the pink color of a medium rare piece of grilled filet mignon at its center the role of being a doctor the shape of this hole. the smell of this portion of mozzarella A continuant that inheres in or is borne by other entities. Every instance of A requires some specific instance of B which must always be the same. b is a relational specifically dependent continuant = Def. b is a specifically dependent continuant and there are n &gt; 1 independent continuants c1, … cn which are not spatial regions are such that for all 1 i &lt; j n, ci and cj share no common parts, are such that for each 1 i n, b s-depends_on ci at every time t during the course of b’s existence (axiom label in BFO2 Reference: [131-004]) b is a specifically dependent continuant = Def. b is a continuant & there is some independent continuant c which is not a spatial region and which is such that b s-depends_on c at every time t during the course of b’s existence. (axiom label in BFO2 Reference: [050-003]) Specifically dependent continuant doesn't have a closure axiom because the subclasses don't necessarily exhaust all possibilites. We're not sure what else will develop here, but for example there are questions such as what are promises, obligation, etc. (iff (RelationalSpecificallyDependentContinuant a) (and (SpecificallyDependentContinuant a) (forall (t) (exists (b c) (and (not (SpatialRegion b)) (not (SpatialRegion c)) (not (= b c)) (not (exists (d) (and (continuantPartOfAt d b t) (continuantPartOfAt d c t)))) (specificallyDependsOnAt a b t) (specificallyDependsOnAt a c t)))))) // axiom label in BFO2 CLIF: [131-004] (iff (SpecificallyDependentContinuant a) (and (Continuant a) (forall (t) (if (existsAt a t) (exists (b) (and (IndependentContinuant b) (not (SpatialRegion b)) (specificallyDependsOnAt a b t))))))) // axiom label in BFO2 CLIF: [050-003] specifically dependent continuant role Role role John’s role of husband to Mary is dependent on Mary’s role of wife to John, and both are dependent on the object aggregate comprising John and Mary as member parts joined together through the relational quality of being married. the priest role the role of a boundary to demarcate two neighboring administrative territories the role of a building in serving as a military target the role of a stone in marking a property boundary the role of subject in a clinical trial the student role A realizable entity the manifestation of which brings about some result or end that is not essential to a continuant in virtue of the kind of thing that it is but that can be served or participated in by that kind of continuant in some kinds of natural, social or institutional contexts. BFO 2 Reference: One major family of examples of non-rigid universals involves roles, and ontologies developed for corresponding administrative purposes may consist entirely of representatives of entities of this sort. Thus ‘professor’, defined as follows,b instance_of professor at t =Def. there is some c, c instance_of professor role & c inheres_in b at t.denotes a non-rigid universal and so also do ‘nurse’, ‘student’, ‘colonel’, ‘taxpayer’, and so forth. (These terms are all, in the jargon of philosophy, phase sortals.) By using role terms in definitions, we can create a BFO conformant treatment of such entities drawing on the fact that, while an instance of professor may be simultaneously an instance of trade union member, no instance of the type professor role is also (at any time) an instance of the type trade union member role (any more than any instance of the type color is at any time an instance of the type length).If an ontology of employment positions should be defined in terms of roles following the above pattern, this enables the ontology to do justice to the fact that individuals instantiate the corresponding universals – professor, sergeant, nurse – only during certain phases in their lives. b is a role means: b is a realizable entity & b exists because there is some single bearer that is in some special physical, social, or institutional set of circumstances in which this bearer does not have to be& b is not such that, if it ceases to exist, then the physical make-up of the bearer is thereby changed. (axiom label in BFO2 Reference: [061-001]) (forall (x) (if (Role x) (RealizableEntity x))) // axiom label in BFO2 CLIF: [061-001] role 1d-s-region OneDimensionalSpatialRegion one-dimensional spatial region an edge of a cube-shaped portion of space. A one-dimensional spatial region is a line or aggregate of lines stretching from one point in space to another. (axiom label in BFO2 Reference: [038-001]) (forall (x) (if (OneDimensionalSpatialRegion x) (SpatialRegion x))) // axiom label in BFO2 CLIF: [038-001] one-dimensional spatial region 3d-s-region ThreeDimensionalSpatialRegion three-dimensional spatial region a cube-shaped region of space a sphere-shaped region of space, A three-dimensional spatial region is a spatial region that is of three dimensions. (axiom label in BFO2 Reference: [040-001]) (forall (x) (if (ThreeDimensionalSpatialRegion x) (SpatialRegion x))) // axiom label in BFO2 CLIF: [040-001] three-dimensional spatial region gdc GenericallyDependentContinuant generically dependent continuant The entries in your database are patterns instantiated as quality instances in your hard drive. The database itself is an aggregate of such patterns. When you create the database you create a particular instance of the generically dependent continuant type database. Each entry in the database is an instance of the generically dependent continuant type IAO: information content entity. the pdf file on your laptop, the pdf file that is a copy thereof on my laptop the sequence of this protein molecule; the sequence that is a copy thereof in that protein molecule. A continuant that is dependent on one or other independent continuant bearers. For every instance of A requires some instance of (an independent continuant type) B but which instance of B serves can change from time to time. b is a generically dependent continuant = Def. b is a continuant that g-depends_on one or more other entities. (axiom label in BFO2 Reference: [074-001]) (iff (GenericallyDependentContinuant a) (and (Continuant a) (exists (b t) (genericallyDependsOnAt a b t)))) // axiom label in BFO2 CLIF: [074-001] generically dependent continuant function Function function the function of a hammer to drive in nails the function of a heart pacemaker to regulate the beating of a heart through electricity the function of amylase in saliva to break down starch into sugar BFO 2 Reference: In the past, we have distinguished two varieties of function, artifactual function and biological function. These are not asserted subtypes of BFO:function however, since the same function – for example: to pump, to transport – can exist both in artifacts and in biological entities. The asserted subtypes of function that would be needed in order to yield a separate monoheirarchy are not artifactual function, biological function, etc., but rather transporting function, pumping function, etc. A function is a disposition that exists in virtue of the bearer’s physical make-up and this physical make-up is something the bearer possesses because it came into being, either through evolution (in the case of natural biological entities) or through intentional design (in the case of artifacts), in order to realize processes of a certain sort. (axiom label in BFO2 Reference: [064-001]) (forall (x) (if (Function x) (Disposition x))) // axiom label in BFO2 CLIF: [064-001] function p-boundary ProcessBoundary process boundary the boundary between the 2nd and 3rd year of your life. p is a process boundary =Def. p is a temporal part of a process & p has no proper temporal parts. (axiom label in BFO2 Reference: [084-001]) Every process boundary occupies_temporal_region a zero-dimensional temporal region. (axiom label in BFO2 Reference: [085-002]) (forall (x) (if (ProcessBoundary x) (exists (y) (and (ZeroDimensionalTemporalRegion y) (occupiesTemporalRegion x y))))) // axiom label in BFO2 CLIF: [085-002] (iff (ProcessBoundary a) (exists (p) (and (Process p) (temporalPartOf a p) (not (exists (b) (properTemporalPartOf b a)))))) // axiom label in BFO2 CLIF: [084-001] process boundary material MaterialEntity material entity a flame a forest fire a human being a hurricane a photon a puff of smoke a sea wave a tornado an aggregate of human beings. an energy wave an epidemic the undetached arm of a human being An independent continuant that is spatially extended whose identity is independent of that of other entities and can be maintained through time. BFO 2 Reference: Material entities (continuants) can preserve their identity even while gaining and losing material parts. Continuants are contrasted with occurrents, which unfold themselves in successive temporal parts or phases [60 BFO 2 Reference: Object, Fiat Object Part and Object Aggregate are not intended to be exhaustive of Material Entity. Users are invited to propose new subcategories of Material Entity. BFO 2 Reference: ‘Matter’ is intended to encompass both mass and energy (we will address the ontological treatment of portions of energy in a later version of BFO). A portion of matter is anything that includes elementary particles among its proper or improper parts: quarks and leptons, including electrons, as the smallest particles thus far discovered; baryons (including protons and neutrons) at a higher level of granularity; atoms and molecules at still higher levels, forming the cells, organs, organisms and other material entities studied by biologists, the portions of rock studied by geologists, the fossils studied by paleontologists, and so on.Material entities are three-dimensional entities (entities extended in three spatial dimensions), as contrasted with the processes in which they participate, which are four-dimensional entities (entities extended also along the dimension of time).According to the FMA, material entities may have immaterial entities as parts – including the entities identified below as sites; for example the interior (or ‘lumen’) of your small intestine is a part of your body. BFO 2.0 embodies a decision to follow the FMA here. A material entity is an independent continuant that has some portion of matter as proper or improper continuant part. (axiom label in BFO2 Reference: [019-002]) Every entity which has a material entity as continuant part is a material entity. (axiom label in BFO2 Reference: [020-002]) every entity of which a material entity is continuant part is also a material entity. (axiom label in BFO2 Reference: [021-002]) (forall (x) (if (MaterialEntity x) (IndependentContinuant x))) // axiom label in BFO2 CLIF: [019-002] (forall (x) (if (and (Entity x) (exists (y t) (and (MaterialEntity y) (continuantPartOfAt x y t)))) (MaterialEntity x))) // axiom label in BFO2 CLIF: [021-002] (forall (x) (if (and (Entity x) (exists (y t) (and (MaterialEntity y) (continuantPartOfAt y x t)))) (MaterialEntity x))) // axiom label in BFO2 CLIF: [020-002] material entity immaterial ImmaterialEntity immaterial entity BFO 2 Reference: Immaterial entities are divided into two subgroups:boundaries and sites, which bound, or are demarcated in relation, to material entities, and which can thus change location, shape and size and as their material hosts move or change shape or size (for example: your nasal passage; the hold of a ship; the boundary of Wales (which moves with the rotation of the Earth) [38, 7, 10 immaterial entity peptide Amide derived from two or more amino carboxylic acid molecules (the same or different) by formation of a covalent bond from the carbonyl carbon of one to the nitrogen atom of another with formal loss of water. The term is usually applied to structures formed from alpha-amino acids, but it includes those derived from any amino carboxylic acid. X = OH, OR, NH2, NHR, etc. peptide deoxyribonucleic acid High molecular weight, linear polymers, composed of nucleotides containing deoxyribose and linked by phosphodiester bonds; DNA contain the genetic information of organisms. deoxyribonucleic acid molecular entity Any constitutionally or isotopically distinct atom, molecule, ion, ion pair, radical, radical ion, complex, conformer etc., identifiable as a separately distinguishable entity. We are assuming that every molecular entity has to be completely connected by chemical bonds. This excludes protein complexes, which are comprised of minimally two separate molecular entities. We will follow up with Chebi to ensure this is their understanding as well molecular entity nucleic acid A macromolecule made up of nucleotide units and hydrolysable into certain pyrimidine or purine bases (usually adenine, cytosine, guanine, thymine, uracil), D-ribose or 2-deoxy-D-ribose and phosphoric acid. nucleic acid ribonucleic acid High molecular weight, linear polymers, composed of nucleotides containing ribose and linked by phosphodiester bonds; RNA is central to the synthesis of proteins. ribonucleic acid macromolecule A macromolecule is a molecule of high relative molecular mass, the structure of which essentially comprises the multiple repetition of units derived, actually or conceptually, from molecules of low relative molecular mass. polymer macromolecule double-stranded DNA double-stranded DNA cell PMID:18089833.Cancer Res. 2007 Dec 15;67(24):12018-25. "...Epithelial cells were harvested from histologically confirmed adenocarcinomas .." A material entity of anatomical origin (part of or deriving from an organism) that has as its parts a maximally connected cell compartment surrounded by a plasma membrane. cell biological_process Any process specifically pertinent to the functioning of integrated living units: cells, tissues, organs, and organisms. A process is a collection of molecular events with a defined beginning and end. biological_process response to stimulus Any process that results in a change in state or activity of a cell or an organism (in terms of movement, secretion, enzyme production, gene expression, etc.) as a result of a stimulus. The process begins with detection of the stimulus and ends with a change in state or activity or the cell or organism. response to stimulus measurement unit label Examples of measurement unit labels are liters, inches, weight per volume. A measurement unit label is as a label that is part of a scalar measurement datum and denotes a unit of measure. 2009-03-16: provenance: a term measurement unit was proposed for OBI (OBI_0000176) , edited by Chris Stoeckert and Cristian Cocos, and subsequently moved to IAO where the objective for which the original term was defined was satisfied with the definition of this, different, term. 2009-03-16: review of this term done during during the OBI workshop winter 2009 and the current definition was considered acceptable for use in OBI. If there is a need to modify this definition please notify OBI. PERSON: Alan Ruttenberg PERSON: Melanie Courtot measurement unit label objective specification In the protocol of a ChIP assay the objective specification says to identify protein and DNA interaction. a directive information entity that describes an intended process endpoint. When part of a plan specification the concretization is realized in a planned process in which the bearer tries to effect the world so that the process endpoint is achieved. 2009-03-16: original definition when imported from OBI read: "objective is an non realizable information entity which can serve as that proper part of a plan towards which the realization of the plan is directed." 2014-03-31: In the example of usage ("In the protocol of a ChIP assay the objective specification says to identify protein and DNA interaction") there is a protocol which is the ChIP assay protocol. In addition to being concretized on paper, the protocol can be concretized as a realizable entity, such as a plan that inheres in a person. The objective specification is the part that says that some protein and DNA interactions are identified. This is a specification of a process endpoint: the boundary in the process before which they are not identified and after which they are. During the realization of the plan, the goal is to get to the point of having the interactions, and participants in the realization of the plan try to do that. Answers the question, why did you do this experiment? PERSON: Alan Ruttenberg PERSON: Barry Smith PERSON: Bjoern Peters PERSON: Jennifer Fostel goal specification OBI Plan and Planned Process/Roles Branch OBI_0000217 objective specification action specification Pour the contents of flask 1 into flask 2 a directive information entity that describes an action the bearer will take Alan Ruttenberg OBI Plan and Planned Process branch action specification datum label A label is a symbol that is part of some other datum and is used to either partially define the denotation of that datum or to provide a means for identifying the datum as a member of the set of data with the same label http://www.golovchenko.org/cgi-bin/wnsearch?q=label#4n GROUP: IAO 9/22/11 BP: changed the rdfs:label for this class from 'label' to 'datum label' to convey that this class is not intended to cover all kinds of labels (stickers, radiolabels, etc.), and not even all kind of textual labels, but rather the kind of labels occuring in a datum. datum label software Software is a plan specification composed of a series of instructions that can be interpreted by or directly executed by a processing unit. see sourceforge tracker discussion at http://sourceforge.net/tracker/index.php?func=detail&aid=1958818&group_id=177891&atid=886178 PERSON: Alan Ruttenberg PERSON: Bjoern Peters PERSON: Chris Stoeckert PERSON: Melanie Courtot GROUP: OBI software data item Data items include counts of things, analyte concentrations, and statistical summaries. a data item is an information content entity that is intended to be a truthful statement about something (modulo, e.g., measurement precision or other systematic errors) and is constructed/acquired by a method which reliably tends to produce (approximately) truthful statements. 2/2/2009 Alan and Bjoern discussing FACS run output data. This is a data item because it is about the cell population. Each element records an event and is typically further composed a set of measurment data items that record the fluorescent intensity stimulated by one of the lasers. 2009-03-16: data item deliberatly ambiguous: we merged data set and datum to be one entity, not knowing how to define singular versus plural. So data item is more general than datum. 2009-03-16: removed datum as alternative term as datum specifically refers to singular form, and is thus not an exact synonym. 2014-03-31: See discussion at http://odontomachus.wordpress.com/2014/03/30/aboutness-objects-propositions/ JAR: datum -- well, this will be very tricky to define, but maybe some information-like stuff that might be put into a computer and that is meant, by someone, to denote and/or to be interpreted by some process... I would include lists, tables, sentences... I think I might defer to Barry, or to Brian Cantwell Smith JAR: A data item is an approximately justified approximately true approximate belief PERSON: Alan Ruttenberg PERSON: Chris Stoeckert PERSON: Jonathan Rees data data item information content entity Examples of information content entites include journal articles, data, graphical layouts, and graphs. A generically dependent continuant that is about some thing. 2014-03-10: The use of "thing" is intended to be general enough to include universals and configurations (see https://groups.google.com/d/msg/information-ontology/GBxvYZCk1oc/-L6B5fSBBTQJ). information_content_entity 'is_encoded_in' some digital_entity in obi before split (040907). information_content_entity 'is_encoded_in' some physical_document in obi before split (040907). Previous. An information content entity is a non-realizable information entity that 'is encoded in' some digital or physical entity. PERSON: Chris Stoeckert OBI_0000142 information content entity 1 1 scalar measurement datum 10 feet. 3 ml. a scalar measurement datum is a measurement datum that is composed of two parts, numerals and a unit label. 2009-03-16: we decided to keep datum singular in scalar measurement datum, as in this case we explicitly refer to the singular form Would write this as: has_part some 'measurement unit label' and has_part some numeral and has_part exactly 2, except for the fact that this won't let us take advantage of OWL reasoning over the numbers. Instead use has measurment value property to represent the same. Use has measurement unit label (subproperty of has_part) so we can easily say that there is only one of them. PERSON: Alan Ruttenberg PERSON: Melanie Courtot scalar measurement datum directive information entity An information content entity whose concretizations indicate to their bearer how to realize them in a process. 2009-03-16: provenance: a term realizable information entity was proposed for OBI (OBI_0000337) , edited by the PlanAndPlannedProcess branch. Original definition was "is the specification of a process that can be concretized and realized by an actor" with alternative term "instruction".It has been subsequently moved to IAO where the objective for which the original term was defined was satisfied with the definitionof this, different, term. 2013-05-30 Alan Ruttenberg: What differentiates a directive information entity from an information concretization is that it can have concretizations that are either qualities or realizable entities. The concretizations that are realizable entities are created when an individual chooses to take up the direction, i.e. has the intention to (try to) realize it. 8/6/2009 Alan Ruttenberg: Changed label from "information entity about a realizable" after discussions at ICBO Werner pushed back on calling it realizable information entity as it isn't realizable. However this name isn't right either. An example would be a recipe. The realizable entity would be a plan, but the information entity isn't about the plan, it, once concretized, *is* the plan. -Alan PERSON: Alan Ruttenberg PERSON: Bjoern Peters directive information entity dot plot Dot plot of SSC-H and FSC-H. A dot plot is a report graph which is a graphical representation of data where each data point is represented by a single dot placed on coordinates corresponding to data point values in particular dimensions. person:Allyson Lister person:Chris Stoeckert OBI_0000123 group:OBI dot plot graph A diagram that presents one or more tuples of information by mapping those tuples in to a two dimensional space in a non arbitrary way. PERSON: Lawrence Hunter person:Alan Ruttenberg person:Allyson Lister OBI_0000240 group:OBI graph algorithm PMID: 18378114.Genomics. 2008 Mar 28. LINKGEN: A new algorithm to process data in genetic linkage studies. A plan specification which describes the inputs and output of mathematical functions as well as workflow of execution for achieving an predefined objective. Algorithms are realized usually by means of implementation as computer programs for execution by automata. Philippe Rocca-Serra PlanAndPlannedProcess Branch OBI_0000270 adapted from discussion on OBI list (Matthew Pocock, Christian Cocos, Alan Ruttenberg) algorithm curation status specification The curation status of the term. The allowed values come from an enumerated list of predefined terms. See the specification of these instances for more detailed definitions of each enumerated value. Better to represent curation as a process with parts and then relate labels to that process (in IAO meeting) PERSON:Bill Bug GROUP:OBI:<http://purl.obolibrary.org/obo/obi> OBI_0000266 curation status specification density plot Density plot of SSC-H and FSC-H. A density plot is a report graph which is a graphical representation of data where the tint of a particular pixel corresponds to some kind of function corresponding the the amount of data points relativelly with their distance from the the pixel. person:Allyson Lister person:Chris Stoeckert OBI_0000179 group:Flow Cytometry community density plot data format specification A data format specification is the information content borne by the document published defining the specification. Example: The ISO document specifying what encompasses an XML document; The instructions in a XSD file 2009-03-16: provenance: term imported from OBI_0000187, which had original definition "A data format specification is a plan which organizes information. Example: The ISO document specifying what encompasses an XML document; The instructions in a XSD file" PERSON: Alan Ruttenberg PlanAndPlannedProcess Branch OBI branch derived OBI_0000187 data format specification data set Intensity values in a CEL file or from multiple CEL files comprise a data set (as opposed to the CEL files themselves). A data item that is an aggregate of other data items of the same type that have something in common. Averages and distributions can be determined for data sets. 2009/10/23 Alan Ruttenberg. The intention is that this term represent collections of like data. So this isn't for, e.g. the whole contents of a cel file, which includes parameters, metadata etc. This is more like java arrays of a certain rather specific type 2014-05-05: Data sets are aggregates and thus must include two or more data items. We have chosen not to add logical axioms to make this restriction. person:Allyson Lister person:Chris Stoeckert data list OBI_0000042 group:OBI data set image An image is an affine projection to a two dimensional surface, of measurements of some quality of an entity or entities repeated at regular intervals across a spatial range, where the measurements are represented as color and luminosity on the projected on surface. person:Alan Ruttenberg person:Allyson person:Chris Stoeckert OBI_0000030 group:OBI image data about an ontology part data about an ontology part is a data item about a part of an ontology, for example a term Person:Alan Ruttenberg data about an ontology part plan specification PMID: 18323827.Nat Med. 2008 Mar;14(3):226.New plan proposed to help resolve conflicting medical advice. A directive information entity with action specifications and objective specifications as parts that, when concretized, is realized in a process in which the bearer tries to achieve the objectives by taking the actions specified. 2009-03-16: provenance: a term a plan was proposed for OBI (OBI_0000344) , edited by the PlanAndPlannedProcess branch. Original definition was " a plan is a specification of a process that is realized by an actor to achieve the objective specified as part of the plan". It has been subsequently moved to IAO where the objective for which the original term was defined was satisfied with the definitionof this, different, term. 2014-03-31: A plan specification can have other parts, such as conditional specifications. Alternative previous definition: a plan is a set of instructions that specify how an objective should be achieved Alan Ruttenberg OBI Plan and Planned Process branch OBI_0000344 2/3/2009 Comment from OBI review. Action specification not well enough specified. Conditional specification not well enough specified. Question whether all plan specifications have objective specifications. Request that IAO either clarify these or change definitions not to use them plan specification measurement datum Examples of measurement data are the recoding of the weight of a mouse as {40,mass,"grams"}, the recording of an observation of the behavior of the mouse {,process,"agitated"}, the recording of the expression level of a gene as measured through the process of microarray experiment {3.4,luminosity,}. A measurement datum is an information content entity that is a recording of the output of a measurement such as produced by a device. 2/2/2009 is_specified_output of some assay? person:Chris Stoeckert OBI_0000305 group:OBI measurement datum setting datum A settings datum is a datum that denotes some configuration of an instrument. 2/3/2009 Feedback from OBI This should be a "setting specification". There is a question of whether it is information about a realizable or not. Pro other specification are about realizables. Cons sometimes specifies a quality which is not a realizable. Alan grouped these in placeholder for the moment. Name by analogy to measurement datum. setting datum conclusion textual entity that fucoidan has a small statistically significant effect on AT3 level but no useful clinical effect as in-vivo anticoagulant, a paraphrase of part of the last paragraph of the discussion section of the paper 'Pilot clinical study to evaluate the anticoagulant activity of fucoidan', by Lowenthal et. al.PMID:19696660 A textual entity that expresses the results of reasoning about a problem, for instance as typically found towards the end of scientific papers. 2009/09/28 Alan Ruttenberg. Fucoidan-use-case 2009/10/23 Alan Ruttenberg: We need to work on the definition still Person:Alan Ruttenberg conclusion textual entity material information bearer A page of a paperback novel with writing on it. The paper itself is a material information bearer, the pattern of ink is the information carrier. a brain a hard drive A material entity in which a concretization of an information content entity inheres. GROUP: IAO material information bearer histogram A histogram is a report graph which is a statistical description of a distribution in terms of occurrence frequencies of different event classes. PERSON:Chris Stoeckert PERSON:James Malone PERSON:Melanie Courtot GROUP:OBI histogram heatmap A heatmap is a report graph which is a graphical representation of data where the values taken by a variable(s) are shown as colors in a two-dimensional map. PERSON:Chris Stoeckert PERSON:James Malone PERSON:Melanie Courtot GROUP:OBI heatmap dendrogram Dendrograms are often used in computational biology to illustrate the clustering of genes. A dendrogram is a report graph which is a tree diagram frequently used to illustrate the arrangement of the clusters produced by a clustering algorithm. PERSON:Chris Stoeckert PERSON:James Malone PERSON:Melanie Courtot WEB: http://en.wikipedia.org/wiki/Dendrogram dendrogram scatter plot Comparison of gene expression values in two samples can be displayed in a scatter plot A scatterplot is a graph which uses Cartesian coordinates to display values for two variables for a set of data. The data is displayed as a collection of points, each having the value of one variable determining the position on the horizontal axis and the value of the other variable determining the position on the vertical axis. PERSON:Chris Stoeckert PERSON:James Malone PERSON:Melanie Courtot scattergraph WEB: http://en.wikipedia.org/wiki/Scatterplot scatter plot obsolescence reason specification The reason for which a term has been deprecated. The allowed values come from an enumerated list of predefined terms. See the specification of these instances for more detailed definitions of each enumerated value. The creation of this class has been inspired in part by Werner Ceusters' paper, Applying evolutionary terminology auditing to the Gene Ontology. PERSON: Alan Ruttenberg PERSON: Melanie Courtot obsolescence reason specification textual entity Words, sentences, paragraphs, and the written (non-figure) parts of publications are all textual entities A textual entity is a part of a manifestation (FRBR sense), a generically dependent continuant whose concretizations are patterns of glyphs intended to be interpreted as words, formulas, etc. AR, (IAO call 2009-09-01): a document as a whole is not typically a textual entity, because it has pictures in it - rather there are parts of it that are textual entities. Examples: The title, paragraph 2 sentence 7, etc. MC, 2009-09-14 (following IAO call 2009-09-01): textual entities live at the FRBR (http://en.wikipedia.org/wiki/Functional_Requirements_for_Bibliographic_Records) manifestation level. Everything is significant: line break, pdf and html versions of same document are different textual entities. PERSON: Lawrence Hunter text textual entity table | T F --+----- T | T F F | F F A textual entity that contains a two-dimensional arrangement of texts repeated at regular intervals across a spatial range, such that the spatial relationships among the constituent texts expresses propositions PERSON: Lawrence Hunter table figure Any picture, diagram or table An information content entity consisting of a two dimensional arrangement of information content entities such that the arrangement itself is about something. PERSON: Lawrence Hunter figure diagram A molecular structure ribbon cartoon showing helices, turns and sheets and their relations to each other in space. A figure that expresses one or more propositions PERSON: Lawrence Hunter diagram document A journal article, patent application, laboratory notebook, or a book A collection of information content entities intended to be understood together as a whole PERSON: Lawrence Hunter document 1 cartesian spatial coordinate datum A cartesian spatial coordinate datum is a representation of a point in a spatial region, in which equal changes in the magnitude of a coordinate value denote length qualities with the same magnitude 2009-08-18 Alan Ruttenberg - question to BFO list about whether the BFO sense of the lower dimensional regions is that they are always part of actual space (the three dimensional sort) http://groups.google.com/group/bfo-discuss/browse_thread/thread/9d04e717e39fb617 Alan Ruttenberg AR notes: We need to discuss whether it should include site. cartesian spatial coordinate datum http://groups.google.com/group/bfo-discuss/browse_thread/thread/9d04e717e39fb617 1 one dimensional cartesian spatial coordinate datum A cartesion spatial coordinate datum that uses one value to specify a position along a one dimensional spatial region Alan Ruttenberg one dimensional cartesian spatial coordinate datum 1 1 two dimensional cartesian spatial coordinate datum A cartesion spatial coordinate datum that uses two values to specify a position within a two dimensional spatial region Alan Ruttenberg two dimensional cartesian spatial coordinate datum 1 1 1 three dimensional cartesian spatial coordinate datum A cartesion spatial coordinate datum that uses three values to specify a position within a three dimensional spatial region Alan Ruttenberg three dimensional cartesian spatial coordinate datum length measurement datum A scalar measurement datum that is the result of measurement of length quality Alan Ruttenberg length measurement datum denotator type The Basic Formal Ontology ontology makes a distinction between Universals and defined classes, where the formal are "natural kinds" and the latter arbitrary collections of entities. A denotator type indicates how a term should be interpreted from an ontological perspective. Alan Ruttenberg Barry Smith, Werner Ceusters denotator type mass measurement datum A scalar measurement datum that is the result of measurement of mass quality 2009/09/28 Alan Ruttenberg. Fucoidan-use-case Person:Alan Ruttenberg mass measurement datum time measurement datum A scalar measurement datum that is the result of measuring a temporal interval 2009/09/28 Alan Ruttenberg. Fucoidan-use-case Person:Alan Ruttenberg time measurement datum documenting Recording the current temperature in a laboratory notebook. Writing a journal article. Updating a patient record in a database. a planned process in which a document is created or added to by including the specified input in it. 6/11/9: Edited at OBI workshop. We need to be able identify a child form of information artifact which corresponds to something enduring (not brain like). This used to be restricted to physical document or digital entity as the output, but that excludes e.g. an audio cassette tape Bjoern Peters wikipedia http://en.wikipedia.org/wiki/Documenting documenting line graph A line graph is a type of graph created by connecting a series of data points together with a line. PERSON:Chris Stoeckert PERSON:Melanie Courtot line chart GROUP:OBI WEB: http://en.wikipedia.org/wiki/Line_chart line graph centrally registered identifier registry PubMed is a CRID registry. It has a dataset of PubMed identifiers associated with journal articles. A CRID registry is a dataset of CRID records, each consisting of a CRID symbol and additional information which was recorded in the dataset through a assigning a centrally registered identifier process. PERSON: Alan Ruttenberg PERSON: Bill Hogan PERSON: Bjoern Peters PERSON: Melanie Courtot CRID registry Original proposal from Bjoern, discussions at IAO calls centrally registered identifier registry time stamped measurement datum time stamped measurement datum time sampled measurement data set pmid:20604925 - time-lapse live cell microscopy A data set that is an aggregate of data recording some measurement at a number of time points. The time series data set is an ordered list of pairs of time measurement data and the corresponding measurement data acquired at that time. Alan Ruttenberg experimental time series time sampled measurement data set software method A software method (also called subroutine, subprogram, procedure, method, function, or routine) is software designed to execute a specific task. PERSON: Melanie Courtot PERSON: Michel Dumontier http://code.google.com/p/information-artifact-ontology/issues/detail?id=80 software method software module A software module is software composed of a collection of software methods. PERSON: Melanei Courtot PERSON: Michel Dumontier http://code.google.com/p/information-artifact-ontology/issues/detail?id=80 software module software library A software library is software composed of a collection of software modules and/or software methods in a form that can be statically or dynamically linked to some software application. PERSON: Melanie Courtot PERSON: Michel Dumontier http://code.google.com/p/information-artifact-ontology/issues/detail?id=80 software library software application A software application is software that can be directly executed by some processing unit. PERSON: Melanie Courtot PERSON: Michel Dumontier http://code.google.com/p/information-artifact-ontology/issues/detail?id=80 software application software script A software script is software whose instructions can be executed using a software interpreter. PERSON: Melanie Courtot PERSON: Michel Dumontier http://code.google.com/p/information-artifact-ontology/issues/detail?id=80 software script Viruses Viruses Bacteria eubacteria Bacteria Archaea Archaea Eukaryota eucaryotes eukaryotes Eukaryota a data transformation that has input of mulitple data and report overall trend of the data. Jie Zheng, Oliver He WEB: https://en.wikipedia.org/wiki/Statistics statistical data analysis a planned process that gathers and measures information on variables of interest, in an established systematic fashion that enables one to answer stated research questions, test hypotheses, and evaluate outcomes. Data collection results in a collection of data. Jie Zheng, Oliver He WEB: http://en.wikipedia.org/wiki/Data_collection data collection A continuous probability distribution that is associated with the f statistic. Yongqun He Fisher-Snedecor distribution WEB: http://stattrek.com/probability-distributions/f-distribution.aspx STATO_0000204 F distribution A continuous probability distribution that is a two-parameter family of continuous probability distributions. Yongqun He WEB: http://en.wikipedia.org/wiki/Gamma_distribution STATO_0000268 gamma distribution A continuous probability distribution that has a symmetrical curve, whose position and shape is determined by its location and scale parameters, the mean and standard deviation respectively. Yongqun He Gaussian distribution WEB: http://en.wikipedia.org/wiki/Normal_distribution STATO_0000227 normal distribution A continuous probability distribution that is is used to estimate population parameters when the sample size is small and/or when the population variance is unknown. Yongqun He t-distribution WEB: http://stattrek.com/probability-distributions/t-distribution.aspx STATO_0000059 Student's t distribution A continuous probability distribution of two variables that has the traditional bell shape and the distribution of one variable is normal to each and every value of the other variable. Marcy Harris bivariate normality WEB: SAS users guide bivariate normal distribution A continuous probability that is the distribution of a random variable X if ln(X) is normally distributed Marcy Harris log normal, lognormal WEB: http://www.statistics.com log-normal distribution A special case of the Pearson product-moment correlation; calculated when either the independent variable or dependent variable is dichotomous while the other variable is non-dichotomous Marcy Harris point biserial correlation An information content entity that refers to a distribution of a random variable that can be described using a mathematical formula. Yongqun He, Jie Zheng WEB: http://en.wikipedia.org/wiki/Probability_distribution probability distribution An information content entity that represents a type of scale on which a variable is measured, including nominal, ordinal, interval, ratio. Marcy Harris level of measurement scale of measure WEB: http://en.wikipedia.org/wiki/Level_of_measurement measurement scale A data item that is numerically distant from the rest of the data; often indicative either measurement error or that the population has a high kurtosis. Marcy Harris, Yongqun He WEB: http://en.wikipedia.org/wiki/Outlier STATO_0000036 outlier A statistic measure that is a function of the samples and considered as a numberical summary of a data-set that reduces the data to one value that can be used to perform a hypothesis test. It can be used to test a finding for statistical signifiance Marcy Harris, Yongqun He WEB: http://en.wikipedia.org/wiki/Test_statistic test statistic A derived data from inferential statistical analysis that is obtained by applying a weighting process to adjust the impact of cases for representing the population from which the data sample is drawn. Marcy Harris WEB: https://www.fedview.opm.gov/2010/reports/weighteddef.htm weighted data A data item that represents a typical value of a set of values. This term relates to the way in which quantitative data tend to cluster around some value. Marcy Harris, Yongqun He WEB: http://en.wikipedia.org/wiki/Central_tendency STATO_0000029 central tendency A data item that is the value that appears most frequent in a set of data. In a normal distribution the numerical value of the mode is the same as that of the mean and median. Marcy Harris WEB: http://en.wikipedia.org/wiki/Mode_%28statistics%29 mode A statistical measure of agreement for categorical data; a measure of inter-rater agreement or inter-annotator agreement. Marcy Harris inter-rater agreement, inter-annotator agreement WEB: http://en.wikipedia.org/wiki/Cohen%27s_kappa cohen's kappa measurement A statistical model that an abstract, quantitative model of the causal dependencies and other interrelationships among observed or hypothetical models; an ordered triple , where U is a set of exogenous variables whose values are determined by factors outside the model; V is a set of endogenous variables whose values are determined by factors within the model; and E is a set of structural equations that express the value of each endogenous variable as a function of the values of the other variables in U and V. Marcy Harris WEB: http://en.wikipedia.org/wiki/Causal_model causal model A measure of the linear association between two variables that are measured on ordinal, interval or ratio scales Marcy Harris WEB: http://www.statistics.com correlation statistical analysis Marcy Harris hierarchical linear model An inferential statistical data analysis that uses measured variation in genes of known function to examine the causal effect of a modifiable exposure on disease in non-experimental studies. Yongqun He, Jie Zheng, Asiyah Yu Lin URL: https://en.wikipedia.org/wiki/Mendelian_randomization Mendelian randomization A statistical model of parameters that vary at more than one level; a type of regression model that explicitly takes into account structured/nested data Marcy Harris hierarchical models multilevel model An inferential statistical data analysis that is used to analyze data that arises from more than one variable Yongqun He, Jie Zheng MVA WEB: http://www.camo.com/multivariate_analysis.html multivariate analysis A data transformation that is used to calculate the power of a statistical analysis. Yongqun He WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms power calculation An inferential statistical data analysis that has only one independent variable Yongqun He univariate analysis An inferential statistical data analysis that analyze the relationship between two measured quantities that renders them statistically dependent Marcy Harris WEB: http://en.wikipedia.org/wiki/Association_%28statistics%29 statistical association A data transformation used in categorical data analysis when the aim is to assess for the presence of an association between a variable with two categories and a variable with k categories. Marcy Harris WEB: http://en.wikipedia.org/wiki/Cochran%E2%80%93Armitage_test_for_trend cochran-armitage test A data transformation that combines categories or ranges of values to produce a smaller number of categories Marcy Harris, Yongqun He bracketing, grouping WEB: SAS users guide data collapsing A measure of the extent to which two variables are associated; the extent to which two random variables vary together Marcy Harris WEB: http://en.wikipedia.org/wiki/Covariation covariation An inferential statistical data analysis used to analyze how well a statistical model fits a set of observations; measures of goodness of fit typically summarize the discrepancy between observed values and the values expected under the model in question. Marcy Harris WEB: http://en.wikipedia.org/wiki/Goodness_of_fit goodness of fit A Kolmogorov-Smirnov test that compares two samples. Marcy Harris, Huan Li, Qingzhi Liu, Oliver He two-sample K-S test two-sample KS test WEB: http://en.wikipedia.org/wiki/Kolmogorov%E2%80%93Smirnov_test Kolmogorov-Smirnov two sample test A data transformation that is specifically an inferential statistic to assess the equality of variances in different sample; tests the null hypothesis that the population variances are equal (called homogeneity of variance or homoscedasticity). Marcy Harris WEB: http://en.wikipedia.org/wiki/Levene%27s_test levene's test A data transformation used for both hypothesis testing and model building to examine the relationship between more than two categorical variables; uses a likelihood ratio statistic that has an approximate chi-square distribution when the sample size is large. Marcy Harris WEB: http://en.wikipedia.org/wiki/Loglinear_analysis loglinear analysis A normal approximation used on nominal data; applied to 2x2 contingency tables to determine whether the row and column marginal frequencies are equal ("marginal homogeneity"). Marcy Harris WEB: http://en.wikipedia.org/wiki/McNemar%27s_test mcnemar's test A directive information entity that represents a mathematical relationship which relates changes in a given response to changes in one or more factors. A statistical model is a formalization of relationships between variables in the form of mathematical equations. Marcy Harris, Yongqun He model WEB: http://www.itl.nist.gov/div898/handbook/pri/section7/pri7.htm; http://en.wikipedia.org/wiki/Statistical_model statistical model Partitioning of the overall variation into assignable components variance components WEB: http://www.itl.nist.gov/div898/handbook/pri/section7/pri7.htm partitioning of variance components A directive information entity that shows how changing the settings of a factor changes the response. The effect of a single factor is also called a main effect. Marcy Harris, Yongqun He effect WEB: http://www.itl.nist.gov/div898/handbook/pri/section7/pri7.htm statistical effect A directive information entity that specifies a data item that can be measured or counted and is used in a statistical analysis. Yongqun He variable WEB: http://en.wikipedia.org/wiki/Variable_%28mathematics%29 WEB: http://www.abs.gov.au/websitedbs/a3121120.nsf/home/statistical+language+-+what+are+variables statistical variable A variable specification that specifies a variable that may have a causal impact on both the independent variable and dependent variable; ignoring a confounding variable may bias empirical estimates of the causal effect of the independent variable. Marcy Harris confounders WEB: http://en.wikipedia.org/wiki/Mediation_%28statistics%29#Mediator_Variable confounding variable specification A variable specification that specifies a variable used in statistical analysis to correct, adjust, or modify the values of a dependent variable; an independent variable not manipulated by the investigator Marcy Harris covariate WEB: http://www.statistics.com covariate specification A variable that has only two categories. Marcy Harris dichotomous variable WEB: SAS users guide dichotomous variable specification A statistical variable with only two categories that reflect only part of the information available in a more comprehensive variable Marcy Harris WEB: SAS users guide dummy variable A variable postulated to be a predictor of one or more dependent variables, and simultaneously predicted by one or more independent variables Marcy Harris intervening variable, mediating variable WEB: SAS Users Guide intervening variable specification A discrete probability distribution that has the number of successes in a sequence of n independent yes/no experiments, each of which yields success with probability p. Such a success/failure experiment is also called a Bernoulli experiment or Bernoulli trial. Yongqun He WEB: http://en.wikipedia.org/wiki/Binomial_distribution binomial distribution A discrete probability distribution that expresses the probability of a given number of events occurring in a fixed interval of time and/or space if these events occur with a known average rate and independently of the time since the last event. The Poisson distribution can also be used for the number of events in other specified intervals such as distance, area or volume. Yongqun He WEB: http://en.wikipedia.org/wiki/Poisson_distribution Poisson distribution A likelihood ratio that is calculated by dividing 1 minus sensitivity by specificity ((1-sensitivity)/specificity). Yongqun He WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms negative likelihood ratio A likelihood ratio that is calculated by dividing sensitivity by 1 minus specificity (sensitivity/(1-specificity)). Yongqun He WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms positive likelihood ratio A data item of an observed or calculated probability of occurrence of an event, X, in a population related to exposure to a specific hazard, infection, trauma; the number of persons suffering from a disease when the exposed population is known with certainty. Yongqun He WEB: http://medical-dictionary.thefreedictionary.com/absolute+risk absolute risk A data item that refers to the number of true positives and true negatives divided by the total number of observations. Yongqun He WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms accuracy A data item collected from censoring that the value of a measurement or observation is only partially known. Marcy Harris, Jie Zheng censoring WEB: https://en.wikipedia.org/wiki/Censoring_(statistics) censored data A probability density function that is for normal distribution probability Jie Zheng, Asiyah Yu Lin, Yongqun He WEB: https://stat.ethz.ch/R-manual/R-devel/library/stats/html/Normal.html f(x) = 1/(√(2 π) σ) e^-((x - μ)^2/(2 σ^2)) normal distribution probability density function A data item that refers to the number of new events that have occurred in a specific time interval divided by the population at risk at the beginning of the time interval. The result gives the likelihood of developing an event in that time interval. Yongqun He incidence WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms Incidence rate A validity that refers to the degree to which evidence and theory support the interpretations of test scores (as entailed by proposed uses of tests). Yongqun He http://en.wikipedia.org/wiki/Validity_(statistics) test validity A data item that refers to the odds that an individual with a specific condition has been exposed to a risk factor divided by the odds that a control has been exposed. The odds ratio is used in case-control studies. The odds ratio provides a reasonable estimate of the relative risk for uncommon conditions. Yongqun He WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms STATO_0000182 odds ratio A data item that refers to the number of individuals with a given disease at a given point in time divided by the population at risk at a specified point in time or over a specified period of time. Yongqun He, Jie Zheng prevalence WEB: http://health.mo.gov/training/epi/PrevalenceRates.html WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms prevalence rate A data item that equals the incidence in exposed individuals divided by the incidence in unexposed individuals. The relative risk can be calculated from studies in which the proportion of patients exposed and unexposed to a risk is known, such as a cohort study. Yongqun He WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms relative risk A data item that refers to the extent to which repeated measurements of a relatively stable phenomenon fall closely to each other. Yongqun He WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms reliability A data item that measures the proportion of actual positives which are correctly identified as such (e.g. the percentage of sick people who are correctly identified as having the condition). Yongqun He sensitivity estimate true positive rate, recall WEB: http://en.wikipedia.org/wiki/Sensitivity_and_specificity STATO_0000233 sensitivity A data item that refers to the proportion of negatives in a binary classification test which are correctly identified Yongqun He true negative rate WEB: http://en.wikipedia.org/wiki/Sensitivity_and_specificity STATO_0000134 specificity A data item that refers to the extent to which a concept conclusion or measurement is well-founded and corresponds accurately to the real world. Yongqun He WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms http://en.wikipedia.org/wiki/Validity_(statistics) Here is another definition: Validity is the extend to which an observation reflects the "truth" of the phenomenon being measured. Reference: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms validity A special case of multiple linear regression in which the relationship between the independent variable x and the dependent variable y is modeled as an nth order polynomial Marcy Harris WEB: http://en.wikipedia.org/wiki/Polynomial_regression polynomial regression A plan specification that provides a detailed outline of which measurements will be taken at what times, on which material, in what manner, and by whom. Sampling plans should be designed in such a way that the resulting data will contain a representative sample of the parameters of interest and allow for all questions, as stated in the goals, to be answered. Marcy Harris sampling design sampling plan WEB: http://www.itl.nist.gov/div898/handbook/ppc/section3/ppc33.htm data sampling design Any method of sampling that uses some form of random selection, that is, one that will ensure that all units in the population have an equal probability or chance of being selected. Marcy Harris WEB: http://srmo.sagepub.com/view/the-sage-dictionary-of-social-research-methods/SAGE.xml random selection A prevalence rate that occurs at a specific period of time. Yongqun He WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms period prevalence rate A prevalence rate that occurs at a specific point of time. Yongqun He WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms point prevalence rate A probability distribution that is associated with continuous variables and has a probability density function. Yongqun He WEB: http://en.wikipedia.org/wiki/Continuous_probability_distribution#Continuous_probability_distribution continuous probability distribution A probability distribution that is associated with discrete variables and is characterized by a probability mass function. Yongqun He WEB: http://en.wikipedia.org/wiki/Continuous_probability_distribution#Discrete_probability_distribution discrete probability distribution A tabular summary of a set of data showing the number of items in each of several non-overlapping classes or groupings Marcy Harris WEB: http://statistics.com frequency distribution A statistical measure of inter-rater agreement or inter-annotator agreement for qualitative (categorical) items. WEB: http://en.wikipedia.org/wiki/Cohen%27s_kappa cohen's kappa coefficient A quantitative confidence value that refers to an interval give values within which there is a high probability (95 percent by convention) that the true population value can be found. The calculation of a confidence interval considers the standard deviation of the data and the number of observations. Thus, a confidence interval narrows as the number of observations increases, or its variance (dispersion) decreases. Yongqun He WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms confidence interval A quantitative confidence value that is used in Bayesian analysis to describe the range in which a posterior probability estimate is likely to reside. Yongqun He WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms credible interval A quantitative confidence value that refers to the upper and lower values defining the central 50 percent of observations. The boundaries are equal to the 25th and 75th percentiles. The interquartile range can be depicted in a box and whiskers plot. Yongqun He WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms interquartile range A quantitative confidence value that equals the percentage of a distribution that is below a specific value. As an example, a child is in 90th percentile for weight if only 10 percent of children the same age weigh more than she does. Yongqun He WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms percentile A quantitative confidence value that refers to the ability of a study to detect a true difference. Negative findings may reflect that the study was underpowered to detect a difference. Yongqun He WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms power A component of experimental error that occurs due to natural variation in the process. Marcy Harris WEB: http://www.itl.nist.gov/div898/handbook/pri/section7/pri7.htm random error A quantitative confidence value that equals the difference between the largest and smallest observation. Yongqun He WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms range A quantitative confidence value that measures the variability of data around the mean. Yongqun He WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms standard deviation A quantitative confidence value that refers to the probability of incorrectly concluding that there is a statistically significant difference in a dataset. Alpha is the number after a p-value. Thus, a statistically significant difference reported as p<0.05 means that there is less than a 5 percent chance that the difference could have occurred by chance. Yongqun He alpha error false positive rate WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms STATO_0000053 type 1 error rate A quantitative confidence value that refers to the probability of incorrectly concluding that there was no statistically significant difference in a dataset. This error often reflects insufficient power of the study. Yongqun He beta error false negative rate WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms STATO_0000220 type 2 error rate A quantitative confidence value that is a general statistical term meaning a systematic (not random) deviation from the true value Marcy Harris WEB: http://www.statistics.com bias A quantitative confidence value that is the standard deviation of a data set divided by the mean of the same data set; a normalized measure of dispersion of a probability distribution Marcy Harris, Yongqun He variation coefficient WEB: http://www.statistics.com coefficient of variation A quantitative confidence value that represents unexplained variation in a collection of observations; comopnents of error include random error and lack of fit error Marcy Harris, Yongqun He error WEB: http://www.itl.nist.gov/div898/handbook/pri/section7/pri7.htm statistical error A quantitative confidence value that represents theoretical average value of a statistic over an infinite number of samples from the same population; the weights correspond to the probabilities in the case of a discrete random variable or densities in the case of a continuous random variable. Marcy Harris WEB: http://en.wikipedia.org/wiki/Expected_value expected value A quantitative confidence value that is a descriptive statistic and can be used to describe how strongly units in the same group resemble each other; unlike other correlation measures it operates on data structured as groups, rather than data structured as paired observations. Marcy Harris, Yongqun He ICC WEB: http://en.wikipedia.org/wiki/Intraclass_correlation intraclass correlation coefficient A quantitative confidence value that has been standardized so that they have variances of 1.0; produces standardized regression coefficients (betas) Marcy Harris WEB: SAS users guide standardized coefficient A type of regression analysis used for predicting the outcome of a categorical dependent variable Marcy Harris logistic regression WEB: http://en.wikipedia.org/wiki/Logistic_regression logit regression A form of regression analysis in which observational data are modeled by a function which is a nonlinear combination of the model parameters and depends on one or more independent variables Marcy Harris WEB: http://en.wikipedia.org/wiki/Nonlinear_regression nonlinear regression A data sampling design that does not use randomization for sample selection Marcy Harris, Jie Zheng, Yongqun He non-randomization sampling plan non-randomization sampling design A data sampling design that uses randomization for sample selection Marcy Harris, Jie Zheng, Yongqun He randomization sampling plan randomization sampling design A measurement scale consisting of equal-sized units; the distance between any two positions is of known size. Marcy Harris WEB: SAS Users Guide WEB: WEB: http://en.wikipedia.org/wiki/Level_of_measurement interval scale A measurement scale that placing of data into categories, without any order or structure (see related OBI term of categorical measurement datum). Marcy Harris http://en.wikipedia.org/wiki/Nominal_scale#Nominal_scale nominal scale A measurement scale that rankings on which data can be sorted however the size or magnitude of differences between any data points in a class is unknown, just that one ranking is greater than the other Marcy Harris WEB: http://en.wikipedia.org/wiki/Nominal_scale#Ordinal_scale ordinal scale A measurement scale that is similar to an interval scale, i.e. a magnitude of a continuous quantity and a unit magnitude of the same kind; the distinguishing feature of a ratio scale is a meaningful zero value that means the absence of whatever is measured. Marcy Harris WEB: http://en.wikipedia.org/wiki/Nominal_scale#Ratio_scale ratio scale A sensitivity that refers to the number of patients with a positive test who have a disease divided by all patients who have the disease. A test with high sensitivity will not miss many patients who have the disease (i.e., few false negative results). Yongqun He WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms disease test sensitivity A specificity that refers to the number of patients who have a negative test and do not have the disease divided by the number of patients who do not have the disease. A test with high specificity will infrequently identify patients as having a disease when they do not (i.e., few false positive results). Yongqun He WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms disease test specificity A statistical effect that is associated with an input variable that has a limited number of levels or in which only a limited number of levels are of interest to the experimenter. Marcy Harris WEB: http://www.itl.nist.gov/div898/handbook/pri/section7/pri7.htm fixed effect A statistical effect that represents the role of a variable in an estimated model (most often a regression model) and its effect on the dependent variable. A variable that has an interaction effect will have a different effect on the dependent variable, depending on the level of some third variable. Marcy Harris moderation WEB: http://www.itl.nist.gov/div898/handbook/pri/section7/pri7.htm interaction effect A statistical effect that is associated with input variables chosen at random from a population having a large or infinite number of possible values. Marcy Harris WEB: http://www.itl.nist.gov/div898/handbook/pri/section7/pri7.htm random effect A statistical error that occurs when the analysis omits one or more important terms or factors from the model. Marcy Harris WEB: http://www.itl.nist.gov/div898/handbook/pri/section7/pri7.htm lack of fit error A statistical error that the null hypothesis is true but has been rejected; a test result that indicates a given condition has been fulfilled, when it actually has not been fulfilled Marcy Harris false positive WEB: http://en.wikipedia.org/wiki/Type_I_and_type_II_errors type I error A statistical error that the null hypothesis is false but has been accepted; a test result indicates that a condition failed, while it actually was successful. Marcy Harris false negative WEB: http://en.wikipedia.org/wiki/Type_I_and_type_II_errors type II error A statistical hypothesis test in which the test statistic has an F-distribution under the null hypothesis Marcy Harris WEB: http://en.wikipedia.org/wiki/F_test F test A non-parametric test of the null hypothesis that two populations are the same against an alternative hypothesis Marcy Harris Wilcoxon rank-sum test WEB: http://en.wikipedia.org/wiki/Mann%E2%80%93Whitney_U mann-whitney U test An experimental design where all cells (i.e. treatment combinations) have the same number of observation Marcy Harris WEB: http://www.itl.nist.gov/div898/handbook/pri/section7/pri7.htm balanced design A study design that starts with the outcome of interest and works backward to the exposure. For instance, patients with a disease are identified and compared with controls for exposure to a risk factor. Yongqun He WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms case-control study design A study design that starts with an exposure and moves forward to the outcome of interest, even if the data are collected retrospectively. As an example, a group of patients who have variable exposure to a risk factor of interest can be followed over time for an outcome. Yongqun He WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms cohort study design A study design in which patients are randomly assigned to two or more interventions. Yongqun He WEB: http://www.uptodate.com/contents/glossary-of-common-biostatistical-and-epidemiological-terms randomized controlled trial design A data sampling design that is designed to generate complex samples where sample members do not have equal probability of being selected. Marcy Harris, Yongqun He, Jie Zheng WEB: http://www.theanalysisfactor.com/complex-sample-what-and-why/ complex sample design A statistic test for several similar measures of agreement used with categorical data; typically used in assessing the degree to which two or more raters, examining the same data, agree on assigning data to categories Marcy Harris WEB: http://www.statistics.com kappa statistic A test statistic of whether k samples are from populations with equal variances. Marcy Harris WEB: http://en.wikipedia.org/wiki/Bartlett%27s_test bartlett's test A statistical variable that specifies a variable describing how, rather than when, effects will occur by accounting for the relationship between the independent and dependent variables. A mediating relationship is one in which the path relating A to C is mediated by a third variable (B). Marcy Harris, Yongqun He intervening variable mediating variable, mediation WEB: http://en.wikipedia.org/wiki/Mediation_%28statistics%29#Mediator_Variable mediating variable A statistical variable that specifies a variable affecting the direction and/or strength of the relation between dependent and independent variables; occurs when the relationship between two variables depends on a third variable Marcy Harris moderator, interaction WEB: http://en.wikipedia.org/wiki/Moderator_variable moderator variable A weighted data that measures the agreement for categorical data; a generalization of the Kappa statistics to situations in which the categories are not equal in some respect so weighted by an objective or subjective function Marcy Harris WEB: http://www.statistics.com weighted kappa A center value that separates the higher half from the lower half of the data sample, population, or probability distribution Marcy Harris WEB: http://en.wikipedia.org/wiki/Median median A statistical model containing both fixed effects and random effects, that is mixed effects; Marcy Harris WEB: http://en.wikipedia.org/wiki/Mixed_model mixed model A data transformation that represents a mathematical function describing the relative likelihood of a continuous random variable to take on a value. Marcy Harris, Yongqun He density function WEB: http://en.wikipedia.org/wiki/Probability_density_function probability density function A data item that represents an arrangement according to a rank, i.e., the position of a particular case relative to other cases on a defined scale. Marcy Harris, Yongqun He WEB: http://www.merriam-webster.com/dictionary/rank%20order rank order A quantitative confidence value that expresses how many times more likely the data are under one model than the other. Yongqun He WEB: http://en.wikipedia.org/wiki/Likelihood-ratio_test likelihood ratio A probability distribution that with k degrees of freedom is the distribution of a sum of the squares of k independent standard normal random variables. Yongqun He WEB: http://en.wikipedia.org/wiki/Chi-square_distribution STATO_0000229 chi-square distribution 2 A data item that is more specifically a rectangular array of numbers, symbols, or expressions, arranged in rows and columns. Person: Oliver He, Jie Zheng set of data sets WEB: https://en.wikipedia.org/wiki/Matrix_(mathematics) data matrix A statistical data analysis that uses patterns in the sample data to draw inferences about the population represented, accounting for randomness. Jie Zheng, Oliver He significantly statistical data analysis WEB: http://en.wikipedia.org/wiki/Statistics inferential statistical data analysis 2 A data item that consists of two or more data sets that are produced as the output of a data transformation. Person: Oliver He, Jie Zheng set of transformed data sets transformed data matrix A data set that is produced as the output of a data transformation. Person: Jie Zheng, Oliver He transformed data set A statistical data analysis objective where the aim is to make inference using population sample data. Jie Zheng, Oliver He inferential statistical data analysis objective A continuous probability distribution that describes the time between events in a Poisson process, i.e. a process in which events occur continuously and independently at a constant average rate. Yongqun He WEB: http://en.wikipedia.org/wiki/Exponential_distribution STATO_0000160 exponential distribution A statistical variable whose value is subject to variations due to chance (i.e. randomness, in a mathematical sense). Jie Zheng, Yongqun He WEB: http://en.wikipedia.org/wiki/Random_variable random variable An objective specification where the aim is to collect data. Jie Zheng, Oliver He data collection objective A data collection process that results in a collection of data generated from an experiment(s). Jie Zheng, Oliver He data collection from experiment A data collection by sampling process that results in a collection of data generated from an survey(s). Jie Zheng, Oliver He data collection from survey A data collection process that results in a collection of data from the literature. Jie Zheng, Oliver He data collection from literature A statistical variable that is manipulated or controlled in a scientific study to test its effect on a dependent variable(s). Jie Zheng, Yongqun He, Barry Smith WEB: http://en.wikipedia.org/wiki/Dependent_and_independent_variables https://www.thoughtco.com/i-ndpendent-and-dependent-variables-differences-606115 independent variable A data collection process that results in a collection of data from a sampling process. Jie Zheng, Oliver He data sampling data collection by sampling A statistical variable that represents the output or effect, or is tested to see if it is the effect in an experiment or a modeling. Jie Zheng, Yongqun He dependent variable WEB: http://en.wikipedia.org/wiki/Dependent_and_independent_variables dependent variable A random variable which can take an infinite number of possible values. Jie Zheng, Yongqun He WEB: http://www.stats.gla.ac.uk/steps/glossary/probability_distributions.html#contvar continuous random variable Examples of discrete random variables include the number of children in a family, the Friday night attendance at a cinema, the number of patients in a doctor's surgery, the number of defective light bulbs in a box of ten. A random variable which may take on only a countable number of distinct values such as 0, 1, 2, 3, 4, ... Jie Zheng, Yongqun He WEB: http://www.stats.gla.ac.uk/steps/glossary/probability_distributions.html#contvar discrete random variable A data item which consists of digits as opposed to letters of the alphabet of special characters Jie Zheng, Yongqun He numeric data WEB: http://www.ask.com/question/what-is-numerical-data numerical data item A plan specification that provides a detailed outline of how data is collected. Jie Zheng, Yongqun He data collection design A validity that refers to the validity of a diagnosis, and associated diagnostic tests or screening tests in a clinical field such as medicine. Yongqun He http://en.wikipedia.org/wiki/Validity_(statistics) diagnostic validity A data collection by sampling process that results in a collection of data generated from an censoring. Jie Zheng, Oliver He data collection by censoring A normalization data transformation that used to create normalized gene expression level from microarray raw data. The raw intensity values are background corrected, log2 transformed and then quantile normalized in the RMA normalization process. Person:Jie Zheng, Oliver He RMA RMA normalization http://www.ncbi.nlm.nih.gov/pubmed/12925520 http://www.molmine.com/magma/loading/rma.htm robust multi-array average normalization An inferential statistical data analysis that is established in 2001 by Virginia Tusher, Robert Tibshirani and Gilbert Chu, for determining whether changes in gene expression are statistically significant. Person: Jie Zheng, Oliver He SAM http://www.ncbi.nlm.nih.gov/pmc/articles/PMC33173/ http://en.wikipedia.org/wiki/Significance_analysis_of_microarrays significance analysis of microarrays A univariate analysis that calculates the level of a desired signal to the level of background noise to identify which detected signal is more signal than noise. It can be used to identify differentially expressed genes. Person: Jie Zheng, Oliver He S2N signal-2-noise statistic http://en.wikipedia.org/wiki/Signal-to-noise_ratio http://www.ncbi.nlm.nih.gov/pubmed/10521349 signal-2-noise statistical analysis A validity that refers to whether an experiment (or a study) is able to scientifically answer the questions it is intended to answer. Yongqun He http://en.wikipedia.org/wiki/Validity_(statistics) experimental validity A quantitative confidence value that indicates how well data points fit a statistical model - sometimes simply a line or curve. It is a statistic used in the context of statistical models whose main purpose is either the prediction of future outcomes or the testing of hypotheses, on the basis of other related information. It provides a measure of how well observed outcomes are replicated by the model, as the proportion of total variation of outcomes explained by the model. Person: Jie Zheng, Oliver He R squared coefficient of determination http://en.wikipedia.org/wiki/Coefficient_of_determination R squared value A data item with a specific table layout that allows visualization of the performance of an algorithm. Each column of the matrix represents the instances in a predicted class, while each row represents the instances in an actual class. Person: Jie Zheng, Oliver He confusion matrix error matrix http://en.wikipedia.org/wiki/Confusion_matrix contingency table A contingency table with two rows and two columns that reports the number of false positives, false negatives, true positives, and true negatives. This allows more detailed analysis than mere proportion of correct guesses (accuracy). Person: Jie Zheng, Oliver He http://en.wikipedia.org/wiki/Confusion_matrix STATO_0000138 2x2 contingency table An inferential statistical data analysis that determines whether an a priori defined set of genes shows statistically significant, concordant differences between two biological states (e.g. phenotypes). Person: Jie Zheng, Oliver He GSEA http://www.pnas.org/content/102/43/15545.abstract Gene Set Enrichment Analysis An inferential statistical data analysis used when comparing two related samples, matched samples, or repeated measurements on a single sample to assess whether their population mean ranks differ (i.e. it is a paired difference test). It can be used as an alternative to the paired Student's t-test, t-test for matched pairs, or the t-test for dependent samples when the population cannot be assumed to be normally distributed. Person: Jie Zheng, Oliver He http://en.wikipedia.org/wiki/Wilcoxon_signed-rank_test Wilcoxon signed-rank test A data collection process that results in a collection of data generated from observation(s). Person: Jie Zheng, Oliver He data collection from observation A data item which is the ratio of observed deaths in the study group to expected deaths in the general population. Person: Jie Zheng, Oliver He SMR http://en.wikipedia.org/wiki/Standardized_mortality_ratio standardized mortality ratio An experimental validity that refers to the degree to which conclusions about the relationship among variables based on the data are correct or ‘reasonable’. Yongqun He http://en.wikipedia.org/wiki/Validity_(statistics) statistical conclusion validity An experimental validity that refers to the degree to which conclusions about causal relationships can be made (e.g. cause and effect), based on the measures used, the research setting, and the whole research design. Yongqun He http://en.wikipedia.org/wiki/Validity_(statistics) internal validity An experimental validity that refers to the extent to which the (internally valid) results of a study can be held to be true for other cases, for example to different people, places or times. In other words, it is about whether findings can be validly generalized. If the same research study was conducted in those other cases, would it get the same results? Yongqun He http://en.wikipedia.org/wiki/Validity_(statistics) external validity An external validity that refers to the extent to which research results can be applied to real life situations outside of research settings. Yongqun He http://en.wikipedia.org/wiki/Validity_(statistics) ecological validity A test validity that refers to the extent to which operationalizations of a construct (i.e., practical tests developed from a theory) do actually measure what the theory says they do. For example, to what extent is a questionnaire actually measuring "intelligence"? Yongqun He http://en.wikipedia.org/wiki/Validity_(statistics) construct validity A construct validity that refers to the degree to which a measure is correlated with other measures that it is theoretically predicted to correlate with. Yongqun He http://en.wikipedia.org/wiki/Validity_(statistics) convergent validity A construct validity that tests whether concepts or measurements that are supposed to be unrelated are, in fact, unrelated. Yongqun He http://en.wikipedia.org/wiki/Validity_(statistics) discriminant validity A test validity that determine whether it covers a representative sample of the behavior domain to be measured through systematic examination of the test content. For example, does an IQ questionnaire have items covering all areas of intelligence discussed in the scientific literature? Yongqun He http://en.wikipedia.org/wiki/Validity_(statistics) content validity A test validity that refers to the correlation between the test and a criterion variable (or variables) taken as representative of the construct. In other words, it compares the test with other measures or outcomes (the criteria) already held to be valid. For example, employee selection tests are often validated against measures of job performance (the criterion), and IQ tests are often validated against measures of academic performance (the criterion). Yongqun He http://en.wikipedia.org/wiki/Validity_(statistics) If the test data and criterion data are collected at the same time, this is referred to as concurrent validity evidence. If the test data are collected first in order to predict criterion data collected at a later point in time, then this is referred to as predictive validity evidence. criterion validity A criterion validity that refers to the degree to which the operationalization correlates with other measures of the same construct that are measured at the same time. When the measure is compared to another measure of the same type, they will be related (or correlated). In the selection test example, this would mean that the tests are administered to current employees and then correlated with their scores on performance reviews. Yongqun He http://en.wikipedia.org/wiki/Validity_(statistics) concurrent validity A criterion validity that refers to the degree to which the operationalization can predict (or correlate with) other measures of the same construct that are measured at some time in the future. With the selection test example, this would mean that the tests are administered to applicants, all applicants are hired, their performance is reviewed at a later time, and then their scores on the two measures are correlated. Yongqun He http://en.wikipedia.org/wiki/Validity_(statistics) predictive validity A content validity that refers to the extent to which an abstract theoretical construct can be turned into a specific practical test. Yongqun He translation validity http://en.wikipedia.org/wiki/Validity_(statistics) representation validity A content validity that estimates whether a test appears to measure a certain criterion. It is not guaranteed that the test actually measures phenomena in that domain. When the test does not appear to be measuring what it is, it has low face validity. Yongqun He translation validity http://en.wikipedia.org/wiki/Validity_(statistics) face validity A software that is used for the differential gene expression significance analysis of DNA microarray experiments for both standard and time course experiments. The outputs consist of bothe p-values and q-values. Elisabetta Manduchi EDGE Storey J.D. (2007) The optimal discovery procedure: A new approach to simultaneous significance testing, Journal of the Royal Statistical Society, Series B, 69: 347-368. Storey J.D., Dai J.Y., and Leek J.T. (2007) The optimal discovery procedure for large-scale significance testing, with applications to comparative microarray experiments, Biostatistics, 8: 414-432. Leek J.T,. Monsen E.C., Dabney A.R., and Storey J.D. (2006) EDGE: Extraction and analysis of differential gene expression, Bioinformatics, 22: 507-508. Storey J.D., Xiao W., Leek J.T., Tompkins R.G., and Davis R.W. (2005) Significance analysis of time course microarray experiments, Proceedings of the National Academy of Sciences, 102: 12837-12842. Beta Cell Biology Consortium Extraction of Differential Gene Expression software A software that can be used to produce lists of differentially expressed genes with confidence measures attached. These lists are generated via a False Discovery Rate (FDR) method of controlling the false positives. Patterns from Gene Expression (PaGE) is more than a differential expression analysis tool. PaGE is a tool to attach descriptive, dependable, and easily interpretable expression patterns to genes across multiple conditions, each represented by a set of replicated array experiments. The input consists of (replicated) intensities from a collection of array experiments from two or more conditions (or from a collection of direct comparisons on 2-channel arrays). The output consists of patterns, one for each row identifier in the data file. One condition is used as a reference to which the other types are compared. The length of a pattern equals the number of non-reference sample types. The symbols in the patterns are integers, where positive integers represent up-regulation as compared to the reference sample type and negative integers represent down-regulation. The patterns are based on the false discovery rates for each position in the pattern, so that the number of positive and negative symbols that appear in each position of the pattern is as descriptive as the data variability allows. The patterns generated are easily interpretable in that integers are used to represent different levels of up- or down-regulation as compared to the reference sample type. Elisabetta Manduchi PaGE PMID:15797908 Grant G.R., Liu J., Stoeckert C.J.Jr. (2005) A practical false discovery rate approach to identifying patterns of differential expression in microarray data, Bioinformatics, 21(11): 2684-2690. Beta Cell Biology Consortium Patterns from Gene Expression software A software that is used to identify transcription factor binding sites in a genome that have been enriched with aligned reads generated from ChIP-Seq technology. Elisabetta Manduchi, Jie Zheng GLITR PMID:19553195 Tuteja G., White P., Schug J., Kaestner K.H. (2009) Extracting transcription factor targets from ChIP-Seq data. Nucleic Acids Res., 37(17): e113. doi: 10.1093/nar/gkp536. Beta Cell Biology Consortium GLobal Identifier of Target Regions software An inferential statistical data analysis to identify protein-binding regions in a genome sequence from the data generated from a ChIP-sequencing or ChIP-chip experiment. When the protein is a transcription factor, the region is a transcription factor binding site (TFBS). Jie Zheng http://en.wikipedia.org/wiki/Peak_calling peak calling A differential expression analysis using LIMMA linear model to identify differential expression for microarray data. Person: Oliver He, Jie Zheng LIMMA LIMMA data analysis Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W and Smyth GK (2015). “limma powers differential expression analyses for RNA-sequencing and microarray studies.” Nucleic Acids Research, 43, pp. doi: 10.1093/nar/gkv007. WEB: http://www.bioconductor.org/packages/release/bioc/html/limma.html differential expression analysis using LIMMA linear models for microarry data A data transformation that add two or more numbers, magnitudes, quantities, or particulars as determined by or as if by the mathematical process of addition. tracker: https://github.com/obcs/obcs/issues/7 Person: Jie Zheng summing data transformation http://dictionary.reference.com/browse/summing PRISM summing data values A data item that is produced as the output of a summing data transformation and represents the total value of the input data. Tracker:https://github.com/obcs/obcs/issues/7 Person: Jie Zheng Jie Zheng PRISM sum value A data collection process that is conducted through an online process. Jie Zheng, Oliver He data collection from online resource An online data collection process that extracts data from an online database Jie Zheng, Oliver He WEB: https://en.wikipedia.org/wiki/Online_database data collection from online database An online data collection process that extracts data from online using a web crawler. A Web crawler is an Internet bot which systematically browses the World Wide Web and gets data from WWW. Jie Zheng, Oliver He data collection using Web spider https://en.wikipedia.org/wiki/Web_crawler data collection by web crawling A data collection process that deals with incommensurate fields in the data. Jie Zheng, Oliver He WEB: http://www.ncbi.nlm.nih.gov/pubmed/26428398 collection of incommensurate data A software that is used to browses the World Wide Web in a methodical, automated manner. Jie Zheng, Yongqun He web crawler web robot web scutter web spider URL: http://www.sciencedaily.com/terms/web_crawler.htm URL: https://en.wikipedia.org/wiki/Web_crawler web crawling software A data transformation process that re-arrange the order of all or part of a set of data items. Jie Zheng, Oliver He WEB: http://stattrek.com/statistics/dictionary.aspx?definition=Permutation WEB: https://en.wikipedia.org/wiki/Permutation permutation A planned process that generates possible values of missing data Jie Zheng, Oliver He WEB: https://www.niehs.nih.gov/about/visiting/events/pastmtg/assets/docs_k_m/missingdatar.r generation of missing data A data transformation process that transforms incompatible data to compatible data. Jie Zheng, Yongqun He WEB: http://en.wikipedia.org/wiki/Loglinear_analysis processing incompatible data A permutation process that randomly orders a set of data items. Jie Zheng, Oliver He WEB: https://en.wikipedia.org/wiki/Random_permutation random permutation A multivariate analysis that uncovers the latent structure (dimensions) of a set of variables. It reduces attribute space from a larger number of variables to a smaller number of factors. Yongqun He, Jie Zheng WEB: https://en.wikipedia.org/wiki/Factor_analysis WEB: https://en.wikipedia.org/wiki/Multivariate_analysis factor analysis A multivariate analysis that compares multivariate sample means. As a multivariate procedure, it is used when there are two or more dependent variables. Yongqun He, Jie Zheng WEB: https://en.wikipedia.org/wiki/Multivariate_analysis_of_variance multivariate analysis of variance MANOVA A regression method of interpolation for which the interpolated values are modeled by a Gaussian process governed by prior covariances, as opposed to a piecewise-polynomial spline chosen to optimize smoothness of the fitted values. Jie Zheng, Yongqun He Gaussian process regression WEB: https://en.wikipedia.org/wiki/Kriging Kriging An inferential statistical data analysis that estimates parameters of an underlying distribution based on the observed distribution Jie Zheng, Oliver He WEB: http://mathworld.wolfram.com/BayesianAnalysis.html Bayesian analysis A random permutation process that generates a permutation of n items uniformly at random without retries. Specifically, it is to start with any permutation (for example, the identity permutation), and then go through the positions 1 through n − 1, and for each position i swap the element currently there with a randomly chosen element from positions i through n, inclusive. Jie Zheng, Oliver He WEB: https://en.wikipedia.org/wiki/Random_permutation knuth shuffle A data transformation process that puts the data items in a set in a certain order. Jie Zheng, Oliver He WEB: https://en.wikipedia.org/wiki/Sorting_algorithm sorting A sorting process that sorts a set of data items based on the numberical order. Jie Zheng, Oliver He WEB: https://en.wikipedia.org/wiki/Sorting_algorithm sorting based on numerical order A sorting process that sorts a set of data items based on a lexicorgraphic order Jie Zheng, Oliver He WEB: https://en.wikipedia.org/wiki/Sorting_algorithm sorting based on lexicorgraphic order A data processing that applies a deterministic mathematical function to each point in a data set; that is, each data point zi is replaced with the transformed value yi = f(zi), where f is a function. Jie Zheng, Yongqun He WEB: https://en.wikipedia.org/wiki/Data_transformation_(statistics) data transformation in statistics A logarithmic transformation that uses the base-2 logarithm. Jie Zheng, Yongqun He WEB: http://en.wikipedia.org/wiki/Logarithm log2 transformation A data transformation that performs an operation of square root. Jie Zheng, Yongqun He WEB: https://en.wikipedia.org/wiki/Square_root square root transformation A variance-stabilizing transformation that transforms a random variable with a Poisson distribution into one with an approximately standard Gaussian distribution. Jie Zheng, Yongqun He WEB: https://en.wikipedia.org/wiki/Anscombe_transform Anscombe transformation A data transformation that lists data items in a sequential arrangement Jie Zheng, Yongqun He rank-order transformation an information content entity that refers to a number value of a data item. Yongqun He, Jie Zheng mathematical data value mathematical value numerical data value A data value that is continuous from an interval of possible outcomes. Yongqun He, Jie Zheng WEB: https://onlinecourses.science.psu.edu/stat414/node/87 continuous data value A data value that is discrete, ie, counted. Yongqun He, Jie Zheng WEB: https://www.mathsisfun.com/data/data-discrete-continuous.html discrete data value A data value that is an ordinal number, ie., a number that tells the position of something in a list. Yongqun He, Jie Zheng ordinal data value A data value that is a cardinal number, i.e., a number that says how many of something there are, such as one, two, three, four, five. Yongqun He, Jie Zheng WEB: https://www.mathsisfun.com/numbers/cardinal-ordinal-nominal.html cardinal data value A mathematic graph that a set of objects (vertices or nodes) that are connected together, where all the edges between two objects are bidirectional. Yongqun He, Jie Zheng undirected network WEB: http://mathinsight.org/definition/undirected_graph undirected graph A data value that is a nominal number, ie., a number used only as a name, or to identify something (not as an actual value or position). Yongqun He, Jie Zheng WEB: https://www.mathsisfun.com/numbers/cardinal-ordinal-nominal.html nominal data value A continuous variable over a particular range of the real numbers is one whose value in that range must be such that, if the variable can take values a and b in that range, then it can also take any value between a and b. We will link continuous variable to measurement scale. Jie Zheng, Yongqun He WEB: https://en.wikipedia.org/wiki/Continuous_and_discrete_variables continuous variable A statistical variable over a particular range of real values is one for which, for any value in the range that the variable is permitted to take on, there is a positive minimum distance to the nearest other permissible value. We will link discrete variable to measurement scale. Jie Zheng, Yongqun He categorical variable WEB: http://www.unesco.org/webworld/idams/advguide/Chapt1_3.htm WEB: https://en.wikipedia.org/wiki/Continuous_and_discrete_variables discrete variable A continuous variable that has order and equal intervals. Jie Zheng, Yongqun He WEB: http://www.unesco.org/webworld/idams/advguide/Chapt1_3.htm interval-scale variable A continuous variable that occur when the measurement is continuous Jie Zheng, Yongqun He WEB: http://www.unesco.org/webworld/idams/advguide/Chapt1_3.htm continuous ordinal variable A continuous variable that is a continuous positive measurement on a nonlinear scale Jie Zheng, Yongqun He WEB: http://www.unesco.org/webworld/idams/advguide/Chapt1_3.htm ratio-scale variable A discrete variable that allows for only qualitative classification Jie Zheng, Yongqun He WEB: http://www.unesco.org/webworld/idams/advguide/Chapt1_3.htm nominal variable A nominal variable, but its different states are ordered in a meaningful sequence Jie Zheng, Yongqun He WEB: http://www.unesco.org/webworld/idams/advguide/Chapt1_3.htm discrete ordinal variable A quantitative variable can be transformed into a categorical variable, called a dummy variable by recoding the values Jie Zheng, Yongqun He WEB: http://www.unesco.org/webworld/idams/advguide/Chapt1_3.htm dummy variable A preference variable is a specific discrete variable, whose value is either in a decreasing or increasing order. Jie Zheng, Yongqun He WEB: http://www.unesco.org/webworld/idams/advguide/Chapt1_3.htm preference variable A discrete variable which can assume more than one value. A typical example is a survey questionnaire about the use of computers in research. The respondents were asked to indicate the purpose(s) for which they use computers in their research work. The respondents could score more than one category. Jie Zheng, Yongqun He WEB: http://www.unesco.org/webworld/idams/advguide/Chapt1_3.htm multiple response variable A probability distribution that represents the probability distribution corresponding to a histogram of data values. Yongqun He, Jie Zheng WEB: https://reference.wolfram.com/language/ref/HistogramDistribution.html histogram distribution A normal distribution that is the distribution of a random variable X for which the Box–Cox transformation on X follows a truncated normal distribution. Yongqun He Gaussian distribution power-normal distribution WEB: http://en.wikipedia.org/wiki/Normal_distribution Box-Cox distribution A mathematic graph that a set of objects (vertices or nodes) that are connected together, where all the edges are directed from one object to another. A directed graph is sometimes called a digraph or a directed network. Yongqun He, Jie Zheng WEB: http://mathinsight.org/definition/directed_graph directed graph A mathematic graph that a set of objects (vertices or nodes) that are connected via numerous semantic relations. Yongqun He, Jie Zheng WEB: http://arxiv.org/abs/1412.2378 relational graph A disposition that inheres in a population of continuant and is realized in a test process (e.g., disease diagnosis). https://jbiomedsem.biomedcentral.com/articles/10.1186/s13326-016-0099-4 AB, JZ, JFE, YH This term is generated in OBCS based on BIPO: https://github.com/OpenLHS/BIPO. See more from OBCS track issue: https://github.com/obcs/obcs/issues/9 Traditionally, sensitivity inheres in a population of material entity like human. However, it raises a concern in the existance of such sensitivity disposition in the context of machine learning using syntheti data generated with mathematical formula. In this case, the population of disposition bearer are not population of organisms or material entities. Here the bearer of the disposition is not independent continuant. sensitivity disposition A mathematic graph that contains a set of objects (vertices or nodes) decomposed into two disjoint sets such that no two objects within the same set are adjacent. Yongqun He, Jie Zheng bigraph WEB: http://mathworld.wolfram.com/BipartiteGraph.html bipartite graph An information content entity that represents a set of objects (vertices or nodes) where some pairs of objects are connected by links. Yongqun He, Jie Zheng WEB: https://en.wikipedia.org/wiki/Graph_(mathematics) mathematic graph A mathematic graph that a set of objects (vertices or nodes) that are connected in a hierarchical from. Yongqun He, Jie Zheng WEB: https://en.wikipedia.org/wiki/Tree_structure hierarchical tree A data item that is derived from a statistical data analysis. Jie Zheng, Yongqun He, Marcy Harris, Asiyah Yu Lin statistic WEB: http://en.wikipedia.org/wiki/Statistic WEB: http://www.ask.com/question/what-is-numerical-data derived data from statistical analysis A data item that is derived from a descriptive statistical data analysis. Jie Zheng, Yongqun He descriptive statistic WEB: http://www.ask.com/question/what-is-numerical-data WEB: https://en.wikipedia.org/wiki/Descriptive_statistics derived data from descriptive statistical analysis A data item that is derived from an inferential statistical data analysis. Jie Zheng, Yongqun He inferential statistic WEB: http://psc.dss.ucdavis.edu/sommerb/sommerdemo/stat_inf/intro.htm WEB: http://www.ask.com/question/what-is-numerical-data derived data from inferential statistical analysis A data transformation process that transforms a data set to a normal distribution. Jie Zheng, Oliver He, Asiyah Yu Lin WEB: https://en.wikipedia.org/wiki/Normal_distribution normal distribution transformation A data set that follows a probability distribution Yongqun He, Jie Zheng, Yu Lin data set following probability distribution A data set that follows a probability distribution Yongqun He, Jie Zheng, Yu Lin normally distributed data set A data set that is an aggregate of numerical data item. Jie Zheng numerical data set A data collection process that results in a collection of data generated from document(s). Jie Zheng, Oliver He data collection from document A data collection process that results in a collection of data generated from eMedical record(s). data collection from eMedical record A rate of deaths (in general, or due to a specific cause) that in a particular population, scaled to the size of that population, per unit of time. Jie Zheng https://en.wikipedia.org/wiki/Mortality_rate mortality rate A rate of unit shif in a hospital. Jie Zheng hospital unit shift rate A data item that is produced as the output of a data transformation. Person: Jie Zheng, Oliver He transformed data item A data transformation in statistics that processes the data matrix collected from eMedical records to a form that is ready for further data analysis. eMedical record data transformation A sensitivity disposition that is related to a medical test and inheres in a population of organism. AB, JZ, JFE, YH medical test sensitivity disposition A statistical hypothesis test that is not based on any parameterized family of probability distributions. QL, YH https://en.wikipedia.org/wiki/Nonparametric_statistics non-parametric test A non-parametric test that was proposed by James Durbin and is used for for balanced incomplete designs. QL, YH https://en.wikipedia.org/wiki/Durbin_test Durbin test A special case of the Durbin test that was proposed by Milton Frieman and is applicable to complete block designs. Friedman test detects the differences in treatments across multiple test attempts. The procedure involves ranking each row (or block) together, then considering the values of ranks by columns. QL, YH, HL https://en.wikipedia.org/wiki/Friedman_test Friedman test An inferential statistical data analysis that includes all randomized patients in the groups to which they were randomly assigned. The intent-to-treat analysis is based on the initial treatment assignment and not on the treatment eventually received. ITT analysis includes every subject who is randomized according to randomized treatment assignment. It ignores noncompliance, protocol deviations, withdrawal, and anything that happens after randomization. HL, QL, YH ITT analysis https://en.wikipedia.org/wiki/Intention-to-treat_analysis https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3159210/ intent-to-treat analysis A non-parametric test of the equality of continuous, one-dimensional probability distributions that can be used to compare a sample with a reference probability distribution (one-sample K–S test), or to compare two samples (two-sample K–S test). The distributions considered under the null hypothesis are continuous distributions but are otherwise unrestricted. HL, QL, YH K-S test KS test https://en.wikipedia.org/wiki/Kolmogorov%E2%80%93Smirnov_test Kolmogorov–Smirnov test A Kolmogorov-Smirnov test that compares a sample with a reference probability distribution. Huan Li, Qingzhi Liu, Oliver He one-sample K-S test one-sample KS test WEB: http://en.wikipedia.org/wiki/Kolmogorov%E2%80%93Smirnov_test Kolmogorov-Smirnov one sample test A non-parametric test that compares the survival distributions of two samples, and iis appropriate to use when the data are right skewed and censored (technically, the censoring must be non-informative). It is widely used in clinical trials to establish the efficacy of a new treatment in comparison with a control treatment when the measurement is the time to event (such as the time from initial treatment to a heart attack). HL, QL, YH KS test Mantel–Cox test log-rank analysis https://en.wikipedia.org/wiki/Log-rank_test log-rank test A chi square test that is applied to sets of categorical data to evaluate how likely it is that any observed difference between the sets arose by chance. It is suitable for unpaired data from large samples. It is also the most widely used of many chi-squared tests. HL, QL, YH Pearson's Chi square test Pearson's X^2 test https://en.wikipedia.org/wiki/Pearson%27s_chi-squared_test Pearson's chi-square test A chi square test that is used in certain situations when testing for independence in a contingency table. In some cases, Yates' correction may adjust too far, and so its current use is limited. HL, QL, YH Yates' correction for continuity https://en.wikipedia.org/wiki/Yates%27s_correction_for_continuity Yates' chi-squared test A chi square test that is used in the analysis of stratified or matched categorical data. It allows an investigator to test the association between a binary predictor or treatment and a binary outcome such as case or control status while taking into account the stratification. Unlike the McNemar test which can only handle pairs, the CMH test handles arbitrary strata size. It is named after William G. Cochran, Nathan Mantel and William Haenszel. HL, QL, YH CMH test https://en.wikipedia.org/wiki/Cochran%E2%80%93Mantel%E2%80%93Haenszel_statistics Cochran–Mantel–Haenszel test A chi square test that is used on paired nominal data. It is applied to 2 × 2 contingency tables with a dichotomous trait, with matched pairs of subjects, to determine whether the row and column marginal frequencies are equal (that is, whether there is "marginal homogeneity"). It is named after Quinn McNemar, who introduced it in 1947. HL, QL, YH CMH test https://en.wikipedia.org/wiki/McNemar%27s_test McNemar's test A data transformation that is used to calculate a ROC curve. Yongqun He, Jie Zheng ROC curve analysis WEB: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3755824/ Receiver operating characteristic curve analysis An inferential statistical data analysis which is used to find the independent components (also called factors, latent variables or sources) by maximizing the statistical independence of the estimated components. Person: Oliver He and Jie Zheng ICA https://en.wikipedia.org/wiki/Independent_component_analysis independent component analysis A regression analysis method that the overall solution minimizes the sum of the squares of the residuals made in the results of every single equation. Person: Jie Zheng https://en.wikipedia.org/wiki/Least_squares least square regression fluorescent reporter intensity A measurement datum that represents the output of a scanner measuring the intensity value for each fluorescent reporter. person:Chris Stoeckert group:OBI From the DT branch: This term and definition were originally submitted by the community to our branch, but we thought they best fit DENRIE. However we see several issues with this. First of all the name 'probe' might not be used in OBI. Instead we have a 'reporter' role. Also, albeit the term 'probe intensity' is often used in communities such as the microarray one, the name 'probe' is ambiguous (some use it to refer to what's on the array, some use it to refer to what's hybed to the array). Furthermore, this concept could possibly be encompassed by combining different OBI terms, such as the roles of analyte, detector and reporter (you need something hybed to a probe on the array to get an intensity) and maybe a more general term for 'measuring intensities'. We need to find the right balance between what is consistent with OBI and combinations of its terms and what is user-friendly. Finally, note that 'intensity' is already in the OBI .owl file and is also in PATO. Why didn't OBI import it from PATO? This might be a problem. fluorescent reporter intensity planned process Injecting mice with a vaccine in order to test its efficacy A processual entity that realizes a plan which is the concretization of a plan specification. 'Plan' includes a future direction sense. That can be problematic if plans are changed during their execution. There are however implicit contingencies for protocols that an agent has in his mind that can be considered part of the plan, even if the agent didn't have them in mind before. Therefore, a planned process can diverge from what the agent would have said the plan was before executing it, by adjusting to problems encountered during execution (e.g. choosing another reagent with equivalent properties, if the originally planned one has run out.) We are only considering successfully completed planned processes. A plan may be modified, and details added during execution. For a given planned process, the associated realized plan specification is the one encompassing all changes made during execution. This means that all processes in which an agent acts towards achieving some objectives is a planned process. Bjoern Peters branch derived 6/11/9: Edited at workshop. Used to include: is initiated by an agent This class merges the previously separated objective driven process and planned process, as they the separation proved hard to maintain. (1/22/09, branch call) planned process biological feature identification objective Biological_feature_identification_objective is an objective role carried out by the proposition defining the aim of a study designed to examine or characterize a particular biological feature. Jennifer Fostel biological feature identification objective classified data set A data set that is produced as the output of a class prediction data transformation and consists of a data set with assigned class labels. PERSON: James Malone PERSON: Monnie McGee data set with assigned class labels classified data set processed material Examples include gel matrices, filter paper, parafilm and buffer solutions, mass spectrometer, tissue samples Is a material entity that is created or changed during material processing. PERSON: Alan Ruttenberg processed material ratio of collected to emitted light 10% A measurement datum measuring the amount of light collected s compared to the total amount of emitted light in the detector component of a flow cytometer instrument. The datum has a qualitative role person:Chris Stoeckert person:Kevin Clancy Submitted by the Flow Cytometry community in DigitalEntity-FlowCytometry-2007-03-30.txt ratio of collected to emitted light investigation Lung cancer investigation using expression profiling, a stem cell transplant investigation, biobanking is not an investigation, though it may be part of an investigation a planned process that consists of parts: planning, study design execution, documentation and which produce conclusion(s). Bjoern Peters OBI branch derived Could add specific objective specification Following OBI call November 2012,26th: it was decided there was no need for adding "achieves objective of drawing conclusion" as existing relations were providing equivalent ability. this note closes the issue and validates the class definition to be part of the OBI core editor = PRS study investigation evaluant role When a specimen of blood is assayed for glucose concentration, the blood has the evaluant role. When measuring the mass of a mouse, the evaluant is the mouse. When measuring the time of DNA replication, the evaluant is the DNA. When measuring the intensity of light on a surface, the evaluant is the light source. a role that inheres in a material entity that is realized in an assay in which data is generated about the bearer of the evaluant role Role call - 17nov-08: JF and MC think an evaluant role is always specified input of a process. Even in the case where we have an assay taking blood as evaluant and outputting blood, the blood is not the specified output at the end of the assay (the concentration of glucose in the blood is) examples of features that could be described in an evaluant: quality.... e.g. "contains 10 pg/ml IL2", or "no glucose detected") GROUP: Role Branch OBI Feb 10, 2009. changes after discussion at OBI Consortium Workshop Feb 2-6, 2009. accepted as core term. evaluant role assay Assay the wavelength of light emitted by excited Neon atoms. Count of geese flying over a house. A planned process with the objective to produce information about the material entity that is the evaluant, by physically examining it or its proxies. 12/3/12: BP: the reference to the 'physical examination' is included to point out that a prediction is not an assay, as that does not require physical examiniation. PlanAndPlannedProcess Branch measuring scientific observation OBI branch derived study assay any method assay quantitative confidence value A data item which is used to indicate the degree of uncertainty about a measurement. person:Chris Stoeckert group:OBI quantitative confidence value diagnosis textual entity diagnosis is an assessment of a disease or injury, its likely prognosis and treatment. Jennifer Fostel diagnosis textual entity eMedical record An eMedical record is a digital document derived from a computer system used primarily for patient care in a clinical setting. Not required to be compliant with requirements of 21 CFR Part 11. person:Jennifer Fostel article-without-pmid-or-doi:CDISCglossary eMedical record reagent role Buffer, dye, a catalyst, a solvating agent. A role inhering in a biological or chemical entity that is intended to be applied in a scientific technique to participate (or have molecular components that participate) in a chemical reaction that facilitates the generation of data about some entity distinct from the bearer, or the generation of some specified material output distinct from the bearer. PERSON:Matthew Brush reagent PERSON:Matthew Brush Feb 10, 2009. changes after discussion at OBI Consortium Workshop Feb 2-6, 2009. accepted as core term. May 28 2013. Updated definition taken from ReO based on discussions initiated in Philly 2011 workshop. Former defnition described a narrower view of reagents in chemistry that restricts bearers of the role to be chemical entities ("a role played by a molecular entity used to produce a chemical reaction to detect, measure, or produce other substances"). Updated definition allows for broader view of reagents in the domain of biomedical research to include larger materials that have parts that participate chemically in a molecular reaction or interaction. (copied from ReO) Reagents are distinguished from instruments or devices that also participate in scientific techniques by the fact that reagents are chemical or biological in nature and necessarily participate in or have parts that participate in some chemical interaction or reaction during their intended participation in some technique. By contrast, instruments do not participate in a chemical reaction/interaction during the technique. Reagents are distinguished from study subjects/evaluants in that study subjects and evaluants are that about which conclusions are drawn and knowledge is sought in an investigation - while reagents, by definition, are not. It should be noted, however, that reagent and study subject/evaluant roles can be borne by instances of the same type of material entity - but a given instance will realize only one of these roles in the execution of a given assay or technique. For example, taq polymerase can bear a reagent role or an evaluant role. In a DNA sequencing assay aimed at generating sequence data about some plasmid, the reagent role of the taq polymerase is realized. In an assay to evaluate the quality of the taq polymerase itself, the evaluant/study subject role of the taq is realized, but not the reagent role since the taq is the subject about which data is generated. In regard to the statement that reagents are 'distinct' from the specified outputs of a technique, note that a reagent may be incorporated into a material output of a technique, as long as the IDENTITY of this output is distinct from that of the bearer of the reagent role. For example, dNTPs input into a PCR are reagents that become part of the material output of this technique, but this output has a new identity (ie that of a 'nucleic acid molecule') that is distinct from the identity of the dNTPs that comprise it. Similarly, a biotin molecule input into a cell labeling technique are reagents that become part of the specified output, but the identity of the output is that of some modified cell specimen which shares identity with the input unmodified cell specimen, and not with the biotin label. Thus, we see that an important criteria of 'reagent-ness' is that it is a facilitator, and not the primary focus of an investigation or material processing technique (ie not the specified subject/evaluant about which knowledge is sought, or the specified output material of the technique). reagent role material processing A cell lysis, production of a cloning vector, creating a buffer. A planned process which results in physical changes in a specified input material PERSON: Bjoern Peters PERSON: Frank Gibson PERSON: Jennifer Fostel PERSON: Melanie Courtot PERSON: Philippe Rocca Serra material transformation OBI branch derived material processing measured expression level Examples are quantified data from an expression microarray experiment, PCR measurements, etc. A measurement datum that is the outcome of the quantification of an assay for the activity of a gene, or the number of RNA transcripts. person:Chris Stoeckert OBI Data Transformation branch measured expression level specimen role liver section; a portion of a culture of cells; a nemotode or other animal once no longer a subject (generally killed); portion of blood from a patient. a role borne by a material entity that is gained during a specimen collection process and that can be realized by use of the specimen in an investigation 22Jun09. The definition includes whole organisms, and can include a human. The link between specimen role and study subject role has been removed. A specimen taken as part of a case study is not considered to be a population representative, while a specimen taken as representing a population, e.g. person taken from a cohort, blood specimen taken from an animal) would be considered a population representative and would also bear material sample role. Note: definition is in specimen creation objective which is defined as an objective to obtain and store a material entity for potential use as an input during an investigation. blood taken from animal: animal continues in study, whereas blood has role specimen. something taken from study subject, leaves the study and becomes the specimen. parasite example - when parasite in people we study people, people are subjects and parasites are specimen - when parasite extracted, they become subject in the following study specimen can later be subject. GROUP: Role Branch OBI specimen role intervention design PMID: 18208636.Br J Nutr. 2008 Jan 22;:1-11.Effect of vitamin D supplementation on bone and vitamin D status among Pakistani immigrants in Denmark: a randomised double-blinded placebo-controlled intervention study. An intervention design is a study design in which a controlled process applied to the subjects (the intervention) serves as the independent variable manipulated by the experimentalist. The treatment (perturbation or intervention) defined can be defined as a combination of values taken by independent variable manipulated by the experimentalists are applied to the recruited subjects assigned (possibly by applying specific methods) to treatment groups. The specificity of intervention design is the fact that independent variables are being manipulated and a response of the biological system is evaluated via response variables as monitored by possibly a series of assays. Philppe Rocca-Serra OBI branch derived intervention design gene list Gene lists may arise from analysis to determine differentially expressed genes, may be collected from the literature for involvement in a particular process or pathway (e.g., inflammation), or may be the input for gene set enrichment analysis. A data set of the names or identifiers of genes that are the outcome of an analysis or have been put together for the purpose of an analysis. person:Chris Stoeckert group:OBI kind of report. (alan) need to be careful to distinguish from output of a data transformation or calculation. A gene list is a report when it is published as such? Relates to question of whether report is a whole, or whether it can be a part of some other narrative object. gene list number of particles in subset 500, 200, 0 A measurement datum measuring the number of subjects in a defined subset in a flow cytometer instrument. The datum has a qualitative role person:Kevin Clancy Submitted by the Flow Cytometry community in DigitalEntity-FlowCytometry-2007-03-30.txt number of particles in subset number of lost events electronic 74, 0, 14 events lost due to data acquisition electronic coincidence. A measurement datum measuring the number of analysis events lost due to errors in data acquisition electronic coincidence in a flow cytometer instrument. The datum has a qualitative role. person:Kevin Clancy Submitted by the Flow Cytometry community in DigitalEntity-FlowCytometry-2007-03-30.txt number of lost events electronic cDNA library PMID:6110205. collection of cDNA derived from mouse splenocytes. Mixed population of cDNAs (complementaryDNA) made from mRNA from a defined source, usually a specific cell type. This term should be associated only to nucleic acid interactors not to their proteins product. For instance in 2h screening use living cells (MI:0349) as sample process. ALT DEF (PRS):: a cDNA library is a collection of host cells, typically E.Coli cells but not exclusively. modified by transfer of plasmid DNA molecule used as vector containing a fragment or totality of cDNA molecule (the insert) . cDNA library may have an array of role and applications. PERSON: Luisa Montecchi PERSON: Philippe Rocca-Serra GROUP: PSI PRS: 22022008. class moved under population, modification of definition and replacement of biomaterials in previous definition with 'material' addition of has_role restriction cDNA library parameter threshold 0.01, 0.03 A measurement datum measuring the minimal signal that must be detected to generate an electrical event, as compared to the maximal detected signal in a flow cytometer instrument. The datum has a qualitative role person:Kevin Clancy Submitted by the Flow Cytometry community in DigitalEntity-FlowCytometry-2007-03-30.txt parameter threshold p-value PMID:19696660 in contrast to the in-vivo data AT-III increased significantly from 113.5% at baseline to 117% after 4 days (n = 10, P-value= 0.02; Table 2). A quantitative confidence value that represents the probability of obtaining a result at least as extreme as that actually obtained, assuming that the actual value was the result of chance alone. May be outside the scope of OBI long term, is needed so is retained PERSON:Chris Stoeckert WEB: http://en.wikipedia.org/wiki/P-value p-value methodology testing objective Methodology_testing_objective is an objective role carried out by a proposition defining the aim of the study is to examine the effect of using different methodologies. Jennifer Fostel methodology testing objective standard error A quantitative confidence value which is the standard deviations of the sample in a frequency distribution, obtained by dividing the standard deviation by the total number of cases in the frequency distribution. person:Chris Stoeckert group:OBI see P-Value standard error software testing objective Software_testing_objective is a hardware_optimization role describing a study designed to examine the effects of using different software or software parameters, e.g. data processing software. Jennifer Fostel software testing objective organization PMID: 16353909.AAPS J. 2005 Sep 22;7(2):E274-80. Review. The joint food and agriculture organization of the United Nations/World Health Organization Expert Committee on Food Additives and its role in the evaluation of the safety of veterinary drug residues in foods. An entity that can bear roles, has members, and has a set of organization rules. Members of organizations are either organizations themselves or individual people. Members can bear specific organization member roles that are determined in the organization rules. The organization rules also determine how decisions are made on behalf of the organization by the organization members. BP: The definition summarizes long email discussions on the OBI developer, roles, biomaterial and denrie branches. It leaves open if an organization is a material entity or a dependent continuant, as no consensus was reached on that. The current placement as material is therefore temporary, in order to move forward with development. Here is the entire email summary, on which the definition is based: 1) there are organization_member_roles (president, treasurer, branch editor), with individual persons as bearers 2) there are organization_roles (employer, owner, vendor, patent holder) 3) an organization has a charter / rules / bylaws, which specify what roles there are, how they should be realized, and how to modify the charter/rules/bylaws themselves. It is debatable what the organization itself is (some kind of dependent continuant or an aggregate of people). This also determines who/what the bearer of organization_roles' are. My personal favorite is still to define organization as a kind of 'legal entity', but thinking it through leads to all kinds of questions that are clearly outside the scope of OBI. Interestingly enough, it does not seem to matter much where we place organization itself, as long as we can subclass it (University, Corporation, Government Agency, Hospital), instantiate it (Affymetrix, NCBI, NIH, ISO, W3C, University of Oklahoma), and have it play roles. This leads to my proposal: We define organization through the statements 1 - 3 above, but without an 'is a' statement for now. We can leave it in its current place in the is_a hierarchy (material entity) or move it up to 'continuant'. We leave further clarifications to BFO, and close this issue for now. PERSON: Alan Ruttenberg PERSON: Bjoern Peters PERSON: Philippe Rocca-Serra PERSON: Susanna Sansone GROUP: OBI organization cluster Cluster of the lymphocytes population. A data set which is a subset of data that are a similar to each other in some way. person:Allyson person:Chris Stoeckert group:OBI cluster organism feature identification objective Organism_feature_identification_objective is a biological_feature_identification_objective role describing a study designed to examine or characterize a biological feature monitored at the level of the organism, e.g. height, weight, stage of development, stage of life cycle. Jennifer Fostel organism feature identification objective number of lost events computer 0, 125, 787 events lost due to computer busy. A measurement datum recording the number of measurement events lost due to overloading of the analysis chip in a flow cytometer instrument. The datum has a qualitative role person:Kevin Clancy Submitted by the Flow Cytometry community in DigitalEntity-FlowCytometry-2007-03-30.txt number of lost events computer protocol PCR protocol, has objective specification, amplify DNA fragment of interest, and has action specification describes the amounts of experimental reagents used (e..g. buffers, dNTPS, enzyme), and the temperature and cycle time settings for running the PCR. A plan specification which has sufficient level of detail and quantitative information to communicate it between investigation agents, so that different investigation agents will reliably be able to independently reproduce the process. PlanAndPlannedProcess Branch OBI branch derived + wikipedia (http://en.wikipedia.org/wiki/Protocol_%28natural_sciences%29) study protocol protocol adding a material entity into a target Injecting a drug into a mouse. Adding IL-2 to a cell culture. Adding NaCl into water. is a process with the objective to place a material entity bearing the 'material to be added role' into a material bearing the 'target of material addition role'. Class was renamed from 'administering substance', as this is commonly used only for additions into organisms. BP branch derived adding a material entity into a target material to be added role drug added to a buffer contained in a tube; substance injected into an animal; material to be added role is a protocol participant role realized by a material which is added into a material bearing the target of material addition role in a material addition process Role Branch OBI 9 March 09 from discussion with PA branch material to be added role drawing a conclusion based on data Concluding that a gene is upregulated in a tissue sample based on the band intensity in a western blot. Concluding that a patient has a infection based on measurement of an elevated body temperature and reported headache. Concluding that there were problems in an investigation because data from PCR and microarray are conflicting. Concluding that 'defects in gene XYZ cause cancer due to improper DNA repair' based on data from experiments in that study that gene XYZ is involved in DNA repair, and the conclusion of a previous study that cancer patients have an increased number of mutations in this gene. A planned process in which data gathered in an investigation is evaluated in the context of existing knowledge with the objective to generate more general conclusions or to conclude that the data does not allow one to draw general conclusion PERSON: Bjoern Peters PERSON: Jennifer Fostel Bjoern Peters drawing a conclusion based on data planning The process of a scientist thinking about and deciding what reagents to use as part of a protocol for an experiment. Note that the scientist could be human or a "robot scientist" executing software. a process of creating or modifying a plan specification 7/18/2011 BP: planning used to itself be a planned process. Barry Smith pointed out that this would lead to an infinite regression, as there would have to be a plan to conduct a planning process, which in itself would be the result of planning etc. Therefore, the restrictions on 'planning' were loosened to allow for informal processes that result in an 'ad hoc plan '. This required changing from 'has_specified_output some plan specifiction' to 'has_participant some plan specification'. Bjoern Peters Bjoern Peters Plans and Planned Processes Branch planning inductive reasoning Based on the observation that all lung cancer patients treated with aspirin in our clinical trial survived longer than the control group, we conclude by inductive reasining that aspirin has a therapeutic effect on lung cancer. a interpreting data that is used to ascribe properties or relations to types based on an observation instance (i.e., on a number of observations or experiences); or to formulate laws based on limited observations of recurring phenomenal patterns. BP: 10/22/122: After changing the parent class to drawing a conclusion *based on data* it is no longer clear that this class is needed; minimally it needs a better definition to distinguish it. Proposal is to obsolete. Bjoern Peters wikipedia: http://en.wikipedia.org/wiki/Inductive_reasoning inductive reasoning hypothesis driven investigation is an investigation with the goal to test one or more hypothesis PlanAndPlannedProcess Branch OBI branch derived hypothesis driven investigation hypothesis generating investigation is an investigation in which data is generated and analyzed with the purpose of generating new hypothesis PlanAndPlannedProcess Branch OBI branch derived hypothesis generating investigation information processor function An information processor function is a function that converts information from one form to another, by a lossless process or an extraction process. Frank Gibson data processor function information processor function cloning vector role pBluescript plays the role of a cloning vector A material to be added role played by a small, self-replicating DNA or RNA molecule - usually a plasmid or chromosome - and realized in a process whereby foreign DNA or RNA is inserted into the vector during the process of cloning. JZ: related tracker: https://sourceforge.net/p/obi/obi-terms/102/ PERSON: Helen Parkinson cloning vector role cloning insert role cloning insert role is a role which inheres in DNA or RNA and is realized by the process of being inserted into a cloning vector in a cloning process. Feb 20, 2009. from Wikipedia: cloning of any DNA fragment essentially involves four steps: DNA fragmentation with restriction endonucleases, ligation of DNA fragments to a vector, transfection, and screening/selection. There are multiple processes involved, it is not just "cloning process" GROUP: Role branch OBII and Wikipedia cloning insert role averaging objective A mean calculation which has averaging objective is a descriptive statistics calculation in which the mean is calculated by taking the sum of all of the observations in a data set divided by the total number of observations. It gives a measure of the 'center of gravity' for the data set. It is also known as the first moment. An averaging objective is a data transformation objective where the aim is to perform mean calculations on the input of the data transformation. Elisabetta Manduchi James Malone PERSON: Elisabetta Manduchi averaging objective adding material objective creating a mouse infected with LCM virus is the specification of an objective to add a material into a target material. The adding is asymmetric in the sense that the target material largely retains its identity BP adding material objective assay objective the objective to determine the weight of a mouse. an objective specification to determine a specified type of information about an evaluated entity (the material entity bearing evaluant role) PPPB branch PPPB branch assay objective target of material addition role peritoneum of an animal receiving an interperitoneal injection; solution in a tube receiving additional material; location of absorbed material following a dermal application. target of material addition role is a role realized by an entity into which a material is added in a material addition process From Branch discussion with BP, AR, MC -- there is a need for the recipient to interact with the administered material. for example, a tooth receiving a filling was not considered to be a target role. GROUP: Role Branch OBI target of material addition role normalized data set A data set that is produced as the output of a normalization data transformation. PERSON: James Malone PERSON: Melanie Courtot normalized data set measure function A glucometer measures blood glucose concentration, the glucometer has a measure function. Measure function is a function that is borne by a processed material and realized in a process in which information about some entity is expressed relative to some reference. PERSON: Daniel Schober PERSON: Helen Parkinson PERSON: Melanie Courtot PERSON:Frank Gibson measure function consume data function Process data function is a function that is borne by in a material entity by virtue of its structure. When realized the material entity consumes data. PERSON: Daniel Schober PERSON: Frank Gibson PERSON: Melanie Courtot consume data function material transformation objective The objective to create a mouse infected with LCM virus. The objective to create a defined solution of PBS. an objective specifiction that creates an specific output object from input materials. PERSON: Bjoern Peters PERSON: Frank Gibson PERSON: Jennifer Fostel PERSON: Melanie Courtot PERSON: Philippe Rocca-Serra artifact creation objective GROUP: OBI PlanAndPlannedProcess Branch material transformation objective study design execution injecting a mouse with PBS solution, weighing it, and recording the weight according to a study design. a planned process that realizes the concretization of a study design removed axiom has_part some (assay or 'data transformation') per discussion on protocol application mailing list to improve reasoner performance. The axiom is still desired. branch derived 6/11/9: edited at workshop. Used to be: study design execution is a process with the objective to generate data according to a concretized study design. The execution of a study design is part of an investigation, and minimally consists of an assay or data transformation. study design execution DNA sequencing Genomic deletions of OFD1 account for 23% of oral-facial-digital type 1 syndrome after negative DNA sequencing. Thauvin-Robinet C, Franco B, Saugier-Veber P, Aral B, Gigot N, Donzel A, Van Maldergem L, Bieth E, Layet V, Mathieu M, Teebi A, Lespinasse J, Callier P, Mugneret F, Masurel-Paulet A, Gautier E, Huet F, Teyssier JR, Tosi M, Frébourg T, Faivre L. Hum Mutat. 2008 Nov 19. PMID: 19023858 DNA sequencing is a sequencing process which uses deoxyribonucleic acid as input and results in a the creation of DNA sequence information artifact using a DNA sequencer instrument. Philippe Rocca-Serra OBI Branch derived nucleotide sequencing DNA sequencing clustered data set A clustered data set is the output of a K means clustering data transformation A data set that is produced as the output of a class discovery data transformation and consists of a data set with assigned discovered class labels. PERSON: James Malone PERSON: Monnie McGee data set with assigned discovered class labels AR thinks could be a data item instead clustered data set data set of features A data set that is produced as the output of a descriptive statistical calculation data transformation and consists of producing a data set that represents one or more features of interest about the input data set. PERSON: James Malone PERSON: Monnie McGee data set of features material combination Mixing two fluids. Adding salt into water. Injecting a mouse with PBS. is a material processing with the objective to combine two or more material entities as input into a single material entity as output. created at workshop as parent class for 'adding material into target', which is asymmetric, while combination encompasses all addition processes. bp bp material combination fuzzy clustering objective A fuzzy clustering objective is a data transformation objective where the aim is to assign input objects (typically vectors of attributes) a probability that a point belongs to a class, where the number of class and their specifications are not known a priori. James Malone PERSON: James Malone PERSON: Ryan Brinkman fuzzy clustering objective data set of predicted values according to fitted curve A data set which is the output of a curve fitting data transformation in which the aim is to find a curve which matches a series of data points and possibly other constraints. PERSON: James Malone PERSON: Monnie McGee data set of predicted values according to fitted curve data representational model gene regulatory graph model phylogenetic tree protein interaction network Data representational model is an information content entity of the relationships between data items. A data representational model is encoded in a data format specification such as for cytoscape or biopax. Melanie Courtot data structure data structure specification GROUP: OBI 2009-02-28: work on this term has been finalized during the OBI workshop winter 2009 data representational model specimen collection process drawing blood from a patient for analysis, collecting a piece of a plant for depositing in a herbarium, buying meat from a butcher in order to measure its protein content in an investigation A planned process with the objective of collecting a specimen. Note: definition is in specimen creation objective which is defined as an objective to obtain and store a material entity for potential use as an input during an investigation. Philly2013: A specimen collection can have as part a material entity acquisition, such as ordering from a bank. The distinction is that specimen collection necessarily involves the creation of a specimen role. However ordering cell lines cells from ATCC for use in an investigation is NOT a specimen collection, because the cell lines already have a specimen role. Philly2013: The specimen_role for the specimen is created during the specimen collection process. label changed to 'specimen collection process' on 10/27/2014, details see tracker: http://sourceforge.net/p/obi/obi-terms/716/ Bjoern Peters specimen collection 5/31/2012: This process is not necessarily an acquisition, as specimens may be collected from materials already in posession 6/9/09: used at workshop specimen collection process background corrected data set A data set that is produced as the output of a background correction data transformation. PERSON: James Malone PERSON: Melanie Courtot background corrected data set error corrected data set A data set that is produced as the output of an error correction data transformation and consists of producing a data set which has had erroneous contributions from the input to the data transformation removed (corrected for). PERSON: James Malone PERSON: Monnie McGee error corrected data set class prediction data transformation A class prediction data transformation (sometimes called supervised classification) is a data transformation that has objective class prediction. James Malone supervised classification data transformation PERSON: James Malone class prediction data transformation background correction data transformation A background correction data transformation (sometimes called supervised classification) is a data transformation that has the objective background correction. James Malone PERSON: James Malone background correction data transformation error correction data transformation An error correction data transformation is a data transformation that has the objective of error correction, where the aim is to remove (correct for) erroneous contributions from the input to the data transformation. James Malone Monnie McGee EDITORS error correction data transformation statistical hypothesis test A statistical hypothesis test data transformation is a data transformation that has objective statistical hypothesis test. James Malone PERSON: James Malone statistical hypothesis test center value A data item that is produced as the output of a center calculation data transformation and represents the center value of the input data. PERSON: James Malone PERSON: Monnie McGee median center value statistical hypothesis test objective is a data transformation objective where the aim is to estimate statistical significance with the aim of proving or disproving a hypothesis by means of some data transformation James Malone Person:Helen Parkinson hypothesis test objective WEB: http://en.wikipedia.org/wiki/Statistical_hypothesis_testing statistical hypothesis test objective reduced dimension data set A data set that is produced as the output of a data vector reduction data transformation and consists of producing a data set which has fewer vectors than the input data set. PERSON: James Malone PERSON: Monnie McGee reduced dimension data set average value A data item that is produced as the output of an averaging data transformation and represents the average value of the input data. PERSON: James Malone PERSON: Monnie McGee arithmetic mean mean average value specimen collection objective The objective to collect bits of excrement in the rainforest. The objective to obtain a blood sample from a patient. A objective specification to obtain a material entity for potential use as an input during an investigation. Bjoern Peters Bjoern Peters specimen collection objective material combination objective is an objective to obtain an output material that contains several input materials. PPPB branch bp material combination objective support vector machine A support vector machine is a data transformation with a class prediction objective based on the construction of a separating hyperplane that maximizes the margin between two data sets of vectors in n-dimensional space. James Malone Ryan Brinkman SVM PERSON: Ryan Brinkman support vector machine self-organizing map A self-organizing map (SOM) is an artificial neural network with objective class discovery that uses a neighborhood function to preserve the topological properties of a dataset to produce low-dimensional (typically 2) discretized representation of the training data set. A set of artificial neurons learn to map points in an input space to coordinates in an output space. The input space can have different dimensions and topology from the output space, and the SOM will attempt to preserve these. James Malone Ryan Brinkman SOM PERSON: Ryan Brinkman self-organizing map decision tree induction objective A decision tree induction objective is a data transformation objective in which a tree-like graph of edges and nodes is created and from which the selection of each branch requires that some type of logical decision is made. James Malone decision tree induction objective decision tree building data transformation A decision tree building data transformation is a data transformation that has objective decision tree induction. James Malone PERSON: James Malone decision tree building data transformation library preparation PMID: 19570239. Construction and analysis of cotton (Gossypium arboreum L.) drought-related cDNA library. Zhang L, Li FG, Liu CL, Zhang CJ, Zhang XY. BMC Res Notes. 2009 Jul 2;2:120. is a process which results in the creation of a library from fragments of DNA using cloning vectors or oligonucleotides with the role of adaptors. Philippe Rocca-Serra library construction library preparation GenePattern software a software that provides access to more than 100 tools for gene expression analysis, proteomics, SNP analysis and common data processing tasks. James Malone Person:Helen Parkinson WEB: http://www.broadinstitute.org/cancer/software/genepattern/ GenePattern software paired-end library PMID: 19339662. Next-generation DNA sequencing of paired-end tags (PET) for transcriptome and genome analyses. Genome Res. 2009 Apr;19(4):521-32. Fullwood MJ, Wei CL, Liu ET, Ruan Y. is a collection of short paired tags from the two ends of DNA fragments are extracted and covalently linked as ditag constructs Philippe Rocca-Serra mate-paired library paired-end tag (PET) library adapted from information provided by Solid web site paired-end library peak matching Peak matching is a data transformation performed on a dataset of a graph of ordered data points (e.g. a spectrum) with the objective of pattern matching local maxima above a noise threshold James Malone Ryan Brinkman PERSON: Ryan Brinkman peak matching k-nearest neighbors A k-nearest neighbors is a data transformation which achieves a class discovery or partitioning objective, in which an input data object with vector y is assigned to a class label based upon the k closest training data set points to y; where k is the largest value that class label is assigned. James Malone k-NN PERSON: James Malone k-nearest neighbors recombinant vector A recombinant vector is created by a recombinant vector cloning process, and contains nucleic acids that can be amplified. It retains functions of the original cloning vector. recombinant vector single fragment library is a collection of short tags from DNA fragments, are extracted and covalently linked as single tag constructs Philippe Rocca-Serra fragment library single fragment library cloning vector A cloning vector is an engineered material that is used as an input material for a recombinant vector cloning process to carry inserted nucleic acids. It contains an origin of replication for a specific destination host organism, encodes for a selectable gene product and contains a cloning site. cloning vector Student's t-test Studen't t-test is a data transformation with the objective of a statistical hypothesis test in which the test statistic has a Student's t distribution if the null hypothesis is true. It is applied when the population is assumed to be normally distributed but the sample sizes are small enough that the statistic on which inference is based is not normally distributed because it relies on an uncertain estimate of standard deviation rather than on a precisely known value. James Malone WEB: http://en.wikipedia.org/wiki/T-test Student's t-test topologically preserved clustered data set the output data set generated from a self-organizing map. A clustered data set in which the topology, i.e. the spatial properties between data points, is preserved from the original input data from which it was derived. James Malone PERSON: James Malone topologically preserved clustered data set CART A CART (classification and regression trees) is a data transformation method for producing a classification or regression model with a tree-based structure. James Malone classification and regression trees BOOK: David J. Hand, Heikki Mannila and Padhraic Smyth (2001) Principles of Data Mining. CART study design independent variable In a study in which gene expression is measured in patients between 8 month to 4 years old that have mild or severe malaria and in which the hypothesis is that gene expression in that age group is a function of disease status, disease status is the independent variable. a directive information entity that is part of a study design. Independent variables are entities whose values are selected to determine its relationship to an observed phenomenon (the dependent variable). In such an experiment, an attempt is made to find evidence that the values of the independent variable determine the values of the dependent variable (that which is being measured). The independent variable can be changed as required, and its values do not represent a problem requiring explanation in an analysis, but are taken simply as given. The dependent variable on the other hand, usually cannot be directly controlled 2/2/2009 Original definition - In the design of experiments, independent variables are those whose values are controlled or selected by the person experimenting (experimenter) to determine its relationship to an observed phenomenon (the dependent variable). In such an experiment, an attempt is made to find evidence that the values of the independent variable determine the values of the dependent variable (that which is being measured). The independent variable can be changed as required, and its values do not represent a problem requiring explanation in an analysis, but are taken simply as given. The dependent variable on the other hand, usually cannot be directly controlled. In the Philly 2013 workshop the label was chosen to distinguish it from "dependent variable" as used in statistical modelling. See: http://en.wikipedia.org/wiki/Statistical_modeling PERSON: Alan Ruttenberg PERSON: Bjoern Peters PERSON: Chris Stoeckert experimental factor independent variable Web: http://en.wikipedia.org/wiki/Dependent_and_independent_variables 2009-03-16: work has been done on this term during during the OBI workshop winter 2009 and the current definition was considered acceptable for use in OBI. If there is a need to modify thisdefinition please notify OBI. study factor study design independent variable study design dependent variable In a study in which gene expression is measured in patients between 8 month to 4 years old that have mild or severe malaria and in which the hypothesis is that gene expression in that age group is a function of disease status, the gene expression is the dependent variable. dependent variable specification is part of a study design. The dependent variable is the event studied and expected to change when the independent variable varies. 2/2/2009 In the design of experiments, independent variables are those whose values are controlled or selected by the person experimenting (experimenter) to determine its relationship to an observed phenomenon (the dependent variable). In such an experiment, an attempt is made to find evidence that the values of the independent variable determine the values of the dependent variable (that which is being measured). The independent variable can be changed as required, and its values do not represent a problem requiring explanation in an analysis, but are taken simply as given. The dependent variable on the other hand, usually cannot be directly controlled. In the Philly 2013 workshop the label was chosen to distinguish it from "dependent variable" as used in statistical modelling. See: http://en.wikipedia.org/wiki/Statistical_modeling PERSON: Alan Ruttenberg PERSON: Bjoern Peters PERSON: Chris Stoeckert dependent variable WEB: http://en.wikipedia.org/wiki/Dependent_and_independent_variables 2009-03-16: work has been done on this term during during the OBI workshop winter 2009 and the current definition was considered acceptable for use in OBI. If there is a need to modify thisdefinition please notify OBI. study design dependent variable survival rate A measurement data that represents the percentage of people or animals in a study or treatment group who are alive for a given period of time after diagnosis or initiation of monitoring. Oliver He adapted from wikipedia http://en.wikipedia.org/wiki/Survival_rate survival rate multiple testing correction objective Application of the Bonferroni correction A multiple testing correction objectives is a data transformation objective where the aim is to correct for a set of statistical inferences considered simultaneously multiple comparison correction objective http://en.wikipedia.org/wiki/Multiple_Testing_Correction multiple testing correction objective statistical model validation Using the expression levels of 20 proteins to predict whether a cancer patient will respond to a drug. A practical goal would be to determine which subset of the 20 features should be used to produce the best predictive model. - wikipedia A data transformation which assesses how the results of a statistical analysis will generalize to an independent data set. Helen Parkinson http://en.wikipedia.org/wiki/Cross-validation_%28statistics%29 statistical model validation spike train datum Measurement of temporal regularity of spike train responses in auditory nerve fibers of the green treefrog A measurement datum which represents information about an ordered series of action potentials in an organism's CNS measured over time. needs more work to see exactly what the data set looks like - HP Helen Parkinson, Alan Ruttenberg spike train measurement Jessica Turner, NIF spike train datum primary structure of DNA macromolecule a quality of a DNA molecule that inheres in its bearer due to the order of its DNA nucleotide residues. placeholder for SO BP et al primary structure of DNA macromolecule measurement device A ruler, a microarray scanner, a Geiger counter. A device in which a measure function inheres. GROUP:OBI Philly workshop OBI measurement device Likelihood-ratio test Likelihood-ratio is a data transformation which tests whether there is evidence of the need to move from a simple model to a more complicated one (where the simple model is nested within the complicated one); tests of the goodness-of-fit between two models. Tina Boussard Likelihood-ratio test pattern matching objective A pattern matching objective aims to detect the presence of the constituents of a given pattern. In contrast to pattern recognition, the pattern is rigidly specified. Patterns are typicall sequences or trees. Tina Boussard http://en.wikipedia.org/wiki/Pattern_matching pattern matching objective study intervention the part of the execution of an intervention design study which is varied between two or more subjects in the study PERSON: Bjoern Peters GROUP: OBI study intervention categorical measurement datum A measurement datum that is reported on a categorical scale Bjoern Peters nominal mesurement datum Bjoern Peters categorical measurement datum handedness assay The Edinburgh handedness assay is a specific method of determing handedness A handedness assay measures the unequal distribution of fine motor skill between the left and right hands typically in human subjects by means of some questionnaire and scoring procedure. Helen Parkinson handedness test http://en.wikipedia.org/wiki/Handedness handedness assay compound treatment design an intervention design in which the treatment is the administration of a compound This is meant to include all kinds of material administrations, including vaccinations, chemical compounds etc. PERSON: Bjoern Peters MO_555 compound_treatment_design compound treatment design categorical label The labels 'positive' vs. 'negative', or 'left handed', 'right handed', 'ambidexterous', or 'strongly binding', 'weakly binding' , 'not binding', or '+++', '++', '+', '-' etc. form scales of categorical labels. A label that is part of a categorical datum and that indicates the value of the data item on the categorical scale. Bjoern Peters Bjoern Peters categorical label device A voltmeter is a measurement device which is intended to perform some measure function. An autoclave is a device that sterlizes instruments or contaminated waste by applying high temperature and pressure. A material entity that is designed to perform a function in a scientific investigation, but is not a reagent. 2012-12-17 JAO: In common lab usage, there is a distinction made between devices and reagents that is difficult to model. Therefore we have chosen to specifically exclude reagents from the definition of "device", and are enumerating the types of roles that a reagent can perform. 2013-6-5 MHB: The following clarifications are outcomes of the May 2013 Philly Workshop. Reagents are distinguished from devices that also participate in scientific techniques by the fact that reagents are chemical or biological in nature and necessarily participate in some chemical interaction or reaction during the realization of their experimental role. By contrast, devices do not participate in such chemical reactions/interactions. Note that there are cases where devices use reagent components during their operation, where the reagent-device distinction is less clear. For example: (1) An HPLC machine is considered a device, but has a column that holds a stationary phase resin as an operational component. This resin qualifies as a device if it participates purely in size exclusion, but bears a reagent role that is realized in the running of a column if it interacts electrostatically or chemically with the evaluant. The container the resin is in (“the column”) considered alone is a device. So the entire column as well as the entire HPLC machine are devices that have a reagent as an operating part. (2) A pH meter is a device, but its electrode component bears a reagent role in virtue of its interacting directly with the evaluant in execution of an assay. (3) A gel running box is a device that has a metallic lead as a component that participates in a chemical reaction with the running buffer when a charge is passed through it. This metallic lead is considered to have a reagent role as a component of this device realized in the running of a gel. In the examples above, a reagent is an operational component of a device, but the device itself does not realize a reagent role (as bearing a reagent role is not transitive across the part_of relation). In this way, the asserted disjointness between a reagent and device holds, as both roles are never realized in the same bearer during execution of an assay. PERSON: Helen Parkinson instrument OBI development call 2012-12-17. device dose specification a protocol specifying to administer 1 ml of vaccine to a mouse a directive information entity that describes the dose that will be administered to a target dose specification 1 scalar score from composite inputs A measurement datum which is the result of combining multiple datum. For example, a mean or summary score. JT: We included this because we wanted to talk about an output from a questionnaire that summarized the answers to the questionnaire, but which was not actually the answer to any single question. Person: Jessica Turner questionaire score Person: Jessica Turner JZ: can we defined it logically as the output of some data transformation, like aggragate data transformation? scalar score from composite inputs sequence data example of usage: the representation of a nucleotide sequence in FASTA format used for a sequence similarity search. A measurement datum that representing the primary structure of a macromolecule(it's sequence) sometimes associated with an indicator of confidence of that measurement. Person:Chris Stoeckert GROUP: OBI sequence data handedness categorical measurement datum A datum used to record the answer to a self assessment of whether a person uses their left hand, right hand primarily or each hand equally PERSON:Alan Ruttenberg PERSON:Jessica Turner handedness categorical measurement datum dose An organism has been injected 1ml of vaccine A measurement datum that measures the quantity of something that may be administered to an organism or that an organism may be exposed to. Quantities of nutrients, drugs, vaccines and toxins are referred to as doses. dose growth condition intervention design A study design in which the independent variable is the environmental condition in which the specimen is growing PERSON: Bjoern Peters MO_588 growth_condition_design growth condition intervention design performing a diagnosis Diagnosing that a patient has pneumonia based on information on measurements of temperature, sound of breathing, and patient complaining about a headache. The interpretation of the information available about bodily features (clinical picture) of a patient resulting in a diagnosis performing a diagnosis 1 Edinburgh score A score that measures the dominance of a person's right or left hand in everyday activities. Person: Alan Ruttenberg Person:Jessica Turner PMID:5146491#Oldfield, R.C. (1971). The assessment and analysis of handedness: The Edinburgh inventory. Neuropsychologia, 9, 97-113 WEB:http://www.cse.yorku.ca/course_archive/2006-07/W/4441/EdinburghInventory.html Edinburgh score administration of material to specimen Staining cells in a tissue slice with a dye. The directed combination of a material entity with a specimen. Bjoern Peters Bjoern Peters administration of material to specimen growth environment The collection of material entities and their qualities that are located near a live organism, tissue or cell and can influence its growth. Right now this may be incomplete. Should also cover e.g. sound, light as well. PERSON:Richard Scheuermann, Jie Zheng, Bjoern Peters OBI group growth environment questionnaire A document with a set of printed or written questions with a choice of answers, devised for the purposes of a survey or statistical study. JT: It plays a role in collecting data that could be fleshed out more; but I'm thinking it is, in itself, an edited document. JZ: based on textual definition of edited document, it can be defined as N&S. I prefer to leave questionnaire as a document now. We can add more restrictions in the future and use that to determine it is an edited document or not. Need to clarify if this is a document or a directive information entity (or what their connection is)) PERSON: Jessica Turner Merriam-Webster questionnaire Edinburgh handedness assay The Edinburgh Handedness assay is an assay in which a set of questions = the Edinburgh Handedness inventory - is asked and the answers to these questions are turned into a score, used to assess the dominance of a person's right or left hand in everyday activities. The inventory can be used by an observer assessing the person, or by a person self-reporting hand use. The latter method tends to be less reliable due to a person over-attributing tasks to the dominant hand. PERSON:Jessica Turner Person:Alan Ruttenberg WEB:http://en.wikipedia.org/wiki/Edinburgh_Handedness_Inventory Edinburgh handedness assay feature extraction A planed process with objective of obtaining quantified values from an image. PERSON: Jie Zheng MO_928: feature_extraction feature extraction binding constant The predicted or measured binding affinity of a peptide to a MHC molecule can be captured in the binding constants "IC50 = 12 nM" or "t 1/2 = 30 minutes". A binding datum about the disposition of two or more material entities to form complexes which comes in the form of a scalar and unit that are utilized in equations that model the binding process 10/6/11 BP: The distinction between binding datum and binding constant is based on the later being part of an equation. That should be captured in the logical definition here, and used to make it to a defined class. PERSON: Bjoern Peters, Randi Vita, Jason Greenbaum binding constant genetically modified material a material entity, organism or cell, that is the output of a genetic transformation process. PERSON: Jie Zheng GROUP: OBI term is proposed by BP on Oct 25, 2010 dev call genetically modified material genetic transformation objective a material transformation objective aims to create genetically modified organism or cell Person: Jie Zheng Person: Jie Zheng suggested to be added by BP and AR during Oct 25, 2010 dev call genetic transformation objective 3D structural organization datum The atom coordinates found in a PDB (Protein Data Bank) file, generated by X Ray crystallography or NMR. A measurement datum that describes the structural orientation of a material entity in 3D space. PERSON: Jason Greenbaum, Randi Vita, Bjoern Peters 3D structural organization datum age since planting measurement datum An age measurement datum that is the result of the measurement of the age of an organism since planting, the process of placing a plant in media (e.g. soil) to allow it to grow, which excludes sowing. PERSON:Chris Stoeckert, Jie Zheng MO_495 planting Discussed by Jie and Chris, proposed to combine with different kinds of processes as initial time point. Proposed 'age measurement assay' is proceeded by some process. The process can be any kind of process defined in OBI. Think it is more flexible. However, it is hard to model due to lake of temporal predicates on Nov 15, 2010 dev call. Term proposed by Bjoern on Nov 8, 2010 dev call Supported by Alan on Nov 15, 2010 dev call age since planting measurement datum age since hatching measurement datum An age measurement datum that is the result of the measurement of the age of an organism since hatching, the process of emergence from an egg. PERSON:Chris Stoeckert, Jie Zheng MO_745 hatching age since hatching measurement datum age measurement assay An assay that measures the duration of temporal interval of a process that is part of the life of the bearer, where the initial time point of the measured process is the beginning of some transitional state of the bearer such as birth or when planted. This assay measures time not developmental stage. we recognize that development takes different time periods under different conditions such as media / temperature. For example, age measurement assay of fly age, the output likes 28 days but not mid-life of age at room temperature. PERSON: Alan Ruttenberg OBI group age measurement assay age since egg laying measurement datum An age measurement datum that is the result of the measurement of the age of an organism since egg laying, the process of the production of egg(s) by an organism. PERSON:Chris Stoeckert, Jie Zheng MO_767 egg laying age since egg laying measurement datum age since germination measurement datum An age measurement datum that is the result of the measurement of the age of an organism since germination, the process consisting of physiological and developmental changes by a seed, spore, pollen grain (microspore), or zygote that occur after release from dormancy, and encompassing events prior to and including the first visible indications of growth. Definition of germination comes from GO. However, the term is deprecated from GO now because it is a grouping term without biological significance. PERSON:Chris Stoeckert, Jie Zheng MO_590 germination age since germination measurement datum age since eclosion measurement datum An age measurement datum that is the result of the measurement of the age of an organism since eclosion, the process of emergence of an adult insect from its pupa or cocoon. PERSON:Chris Stoeckert, Jie Zheng MO_876 eclosion age since eclosion measurement datum age since sowing measurement datum An age measurement datum that is the result of the measurement of the age of an organism since sowing, the process of placing a seed or spore in some media with the intention to invoke germination. PERSON:Chris Stoeckert, Jie Zheng MO_748 sowing age since sowing measurement datum age since coitus measurement datum An age measurement datum that is the result of the measurement of the age of an organism since coitus, the process of copulation that occurs during the process of sexual reproduction. PERSON:Chris Stoeckert, Jie Zheng MO_783 coitus age since coitus measurement datum age measurement datum A time measurement datum that is the result of measurement of age of an organism note that we are currently defining subtypes of age measurement datum that specify when the age is relative to, e.g. planting, as we don't have adequate temporal predicates yet. life of bearer doesn't imply organism this assay measures time not developmental stage. we recognize that development can take different time periods under different conditions such as media / temperature age as a quality is dubious; we plan to revisit stages in development are currently handled with controlled vocabulary, such as 2-somite stage PERSON: Alan Ruttenberg, Chris Stoeckert, Jie Zheng MO_178 Age In MageTab file, we use initialTimePoint (a process) + age (a number expected) + TimeUnit (definied in UO, such as year, hour, day, etc.) Now we use the term label indicating the start time point of measuring the age, (number + TimeUnit) are expected instances of the class discussed on Nov 15, dev call All subtype will be defined by textual definition now. age measurement datum age since fertilization measurement datum An age measurement datum that is the result of the measurement of the age of an organism since fertilization, the process of the union of gametes of opposite sexes during the process of sexual reproduction to form a zygote. Definition of fertilization comes from GO. PERSON:Chris Stoeckert, Jie Zheng MO_701 fertilization age since fertilization measurement datum age since birth measurement datum An age measurement datum that is the result of the measurement of the age of an organism since birth, the process of emergence and separation of offspring from the mother. PERSON:Chris Stoeckert, Jie Zheng MO_710 birth age since birth measurement datum half life datum (t 1/2) The time it takes for 50% of a class of stochastic processes to occur. Bjoern Peters t 1/2 Bjoern Peters half life datum (t 1/2) dose response curve A data item of paired values, one indicating the dose of a material, the other quantitating a measured effect at that dose. The dosing intervals are chosen so that effect values be interpolated by a plotting a curve. Bjoern Peters; Randi Vita dose response curve half maximal effective concentration (EC50) Determining the potentency of a drug / antibody / toxicant by measuring a graded dose response curve, and determining the concentration of the compound where 50% of its maximal effect is observed. half maximal effective concentration (EC50) is a scalar measurement datum corresponding to the concentration of a compound which induces a response halfway between the baseline and maximum after some specified exposure time. Bjoern Peters; Randi Vita wikipedia half maximal effective concentration (EC50) binding datum A data item that states if two or more material entities have the disposition to form a complex, and if so, how strong that disposition is. Bjoern Peters; Randi Vita binding datum negative binding datum A binding datum that states that there is no significant disposition of two or more entities to form a complex negative binding datum half maximal inhibitory concentration (IC50) Interpolating that at a dose of IC50=12 nM, half of the binding of a comptetitive ligand is inhibited. Half maximal inhibitory concentration (IC50) is a scalar measurement datum that measures the effectiveness of a compound to competitively inhibit a given process, and corresponds to the concentration of the compound at which it reaches half of its maximum inhibitory effect. Bjoern Peters; Randi Vita wikipedia half maximal inhibitory concentration (IC50) normalization testing design A study design that tests different normalization procedures. Person: Chris Stoeckert, Jie Zheng MO_729 normalization_testing_design normalization testing design genetic population background information genotype information 'C57BL/6J Hnf1a+/-' in this case, C57BL/6J is the genetic population background information a genetic characteristics information which is a part of genotype information that identifies the population of organisms proposed and discussed on San Diego OBI workshop, March 2011 Group: OBI group Group: OBI group genetic population background information FWER adjusted p-value http://ugrad.stat.ubc.ca/R/library/LPE/html/mt.rawp2adjp.html A quantitative confidence value resulting from a multiple testing error correction method which adjusts the p-value used as input to control for Type I error in the context of multiple pairwise tests PERS:Philippe Rocca-Serra adapted from wikipedia (http://en.wikipedia.org/wiki/Familywise_error_rate) FWER adjusted p-value wild type organism genotype information C57BL/6J wild type a genotype information about an organism and includes information that there are no known modifications to the genetic background. Generally it is the genotype information of a representative individual from a class of organisms. proposed and discussed on San Diego OBI workshop, March 2011 Group: OBI group Group: OBI group wild type organism genotype information genotype information Genotype information can be: Mus musculus wild type (in this case the genetic population background information is Mus musculus), C57BL/6J Hnf1a+/- (in this case, C57BL/6J is the genetic population background information and Hnf1a+/- is the allele information a genetic characteristics information that is about the genetic material of an organism and minimally includes information about the genetic background and can in addition contain information about specific alleles, genetic modifications, etc. discussed on San Diego OBI workshop, March 2011 Group: OBI group Group: OBI group genotype information allele information genotype information 'C57BL/6J Hnf1a+/-' in this case, Hnf1a+/- is the allele information a genetic alteration information that about one of two or more alternative forms of a gene or marker sequence and differing from other alleles at one or more mutational sites based on sequence. Polymorphisms are included in this definition. discussed on San Diego OBI workshop, March 2011 Person: Chris Stoeckert, Jie Zheng MO_58 Allele allele information post-transcriptional modification design A study design in which a modification of the transcriptome, proteome (not genome) is made, for example RNAi, antibody targeting. Person: Chris Stoeckert, Jie Zheng MO_392 cellular_modification_design post transcription modification design? or more clear RNAi design / antibody targeting design? need to check the use cases post-transcriptional modification design genetic alteration information a genetic characteristics information that is about known changes or the lack thereof from the genetic background, including allele information, duplication, insertion, deletion, etc. proposed and discussed on San Diego OBI workshop, March 2011 Group: OBI group Group: OBI group genetic alteration information wild type allele information an allele information that is about the allele found most frequently in natural populations, or in standard laboratory stocks for a given organism. discussed on San Diego OBI workshop, March 2011 Person: Chris Stoeckert, Jie Zheng MO_605 genotype wild type allele information stimulus or stress design A study design in which the response of an organism(s) to the stress or stimulus is studied, e.g. osmotic stress, heat shock, radiation exposure, behavioral treatment etc. Person: Chris Stoeckert, Jie Zheng MO_568 stimulus_or_stress_design stimulus or stress design genetic characteristics information a data item that is about genetic material including polymorphisms, disease alleles, and haplotypes. Person: Chris Stoeckert, Jie Zheng MO_66 IndividualGeneticCharacteristics MO definition: The genotype of the individual organism from which the biomaterial was derived. Individual genetic characteristics include polymorphisms, disease alleles, and haplotypes. examples in ArrayExpress wild_type MutaMouse (CD2F1 mice with lambda-gt10LacZ integration) AlfpCre; SNF5 flox/knockout p53 knock out C57Bl/6 gp130lox/lox MLC2vCRE/+ fer-15; fem-1 df/df pat1-114/pat1-114 ade6-M210/ade6-M216 h+/h+ (cells are diploid) genetic characteristics information dose response design A study design that examines the relationship between the size of the administered dose and the extent of the response. Person: Chris Stoeckert, Jie Zheng MO_485 dose_response_design dose response design q-value PMID: 20483222. Comp Biochem Physiol Part D Genomics Proteomics. 2008 Sep;3(3):234-42. Analysis of Sus scrofa liver proteome and identification of proteins differentially expressed between genders, and conventional and genetically enhanced lines. "After controlling the false discovery rate (FDR</=0.1) using the Storey q value only four proteins (EPHX1, CAT, PAH, ST13) were shown to be differentially expressed between genders (Males/Females) and two proteins (SELENBP2, TAGLN) were differentially expressed between two lines (Transgenic/Conventional pigs)" A quantitative confidence value that measures the minimum false discovery rate that is incurred when calling that test significant. To compute q-values, it is necessary to know the p-value produced by a test and possibly set a false discovery rate level. PERS:Philippe Rocca-Serra FDR adjusted p-value Adapted from several sources, including http://.en/wikipedia.org/wiki/False_discovery_rate http://svitsrv25.epfl.ch/R-doc/library/qvalue.html q-value genetic modification design A study design in which an organism(s) is studied that has had genetic material removed, rearranged, mutagenized or added, such as in a knock out. Person: Chris Stoeckert, Jie Zheng MO_447 genetic_modification_design genetic modification design lowess group transformation A lowess transformation where a potentially different normalization curve is generated and used for two or more groups (delineated by some criteria); criteria could include blocks (e.g. print-tip groups) on an array, or the day on which mass spectrometry was performed. Person: Elisabetta Manduchi MO_861 lowess_group_normalization lowess group transformation lowess transformation A data transformation of normalizing ratio data by using a locally weighted polynomial regression (typically after a log transformation). The regression can be performed on log ratios resulting from the relation of two data sets versus the average log intensity data from the same two data sets or it can be performed on raw or log transformed values from one data set versus values from another. The goal could be to remove intensity-dependent dye-specific effects from the set of pair wise ratios. This method can be applied globally, or limited by one or more specified criteria. Person: Elisabetta Manduchi MO_720 lowess_normalization lowess transformation lowess global transformation A lowess transformation where the same normalization curve is used for all members of the data set; e.g. Features on an array, picked spots on a gel, or measured metabolites in a sample. Person: Elisabetta Manduchi MO_692 lowess_global_normalization lowess global transformation sampling time measurement datum A time measurement datum when an observation is made or a sample is taken from a material as measured from some reference point. Person: Chris Stoeckert time point MO_738 timepoint sampling time measurement datum minimal inhibitory concentration A scalar measurement datum that indicates the lowest concentration at which a specific compound significantly inhibits a process from occurring compared to in the absence of the compound. Created following request by Albert Goldfain PERSON:Bjoern Peters Bjoern Peters, coordinated with Albert Goldfain minimal inhibitory concentration sequence assembly algorithm An algorithm used to assemble individual sequence reads into larger contiguous sequences (contigs). Assembly details include but are not limited to assembler type (overlap-layout-consensus, deBruijn), assembler version, and any relevant quality control information such as per cent known genes/ESTs captured. Person: Chris Stoeckert, Jie Zheng NIAID GSCID-BRC metadata working group Assembly Algorithm NIAID GSCID-BRC sequence assembly algorithm PDB file The file found in the pdb with the identifier 3pe4 http://www.pdb.org/pdb/download/downloadFile.do?fileFormat=pdb&compression=NO&structureId=3pe4 A 3d structural organization datum capturing the results of X-ray crystallography or NMR experiment that is formatted as specified by the Protein Databank (http://www.wwpdb.org/docs.html). A PDB file can describe the structure of multiple molecules, each of which has a different chain identifier assigned. PERSON: Bjoern Peters, Dorjee Tamang, Jason Greenbaum PDB file equilibrium dissociation constant (KD) KD = 32 nM is the equilibrium dissociation rate found for peptide SIINFEKL binding to H-2 Kb A binding constant defined as the ratio of kon over koff (on-rate of binding divided by off-rate) PERSON: Bjoern Peters, Randi Vita IEDB equilibrium dissociation constant (KD) comparative phenotypic assessment Interpreting data from assays that evaluate the qualities or dispositions inhering in an organism or organism part and comparing it to data from other organisms to make a conclusion about a phenotypic difference Philly workshop 2011 Philly workshop 2011 6/1/2012: We will utilize 'comparative qualities' once they are available in BFO2 comparative phenotypic assessment equilibrium association constant (KA) KA = 10^-12 M^-1 is the equilibirum association constant maximally found for antibody binding to haptens. A binding constant defined as the ratio of koff over kon (off-rate of binding divided by on-rate) PERSON: Bjoern Peters, Randi Vita IEDB equilibrium association constant (KA) rate measurement datum The rate of disassociation of a peptide from a complex with an MHC molecule measured by the ratio of bound and unbound peptide per unit of time. A scalar measurement datum that represents the number of events occuring over a time interval PERSON: Bjoern Peters, Randi Vita IEDB rate measurement datum 50% dissociation of binding temperature (Tm) Preparing a complex of a purified HLA-A*02:01 bound to a specific peptide ligand, varying the temperature while detecting the fraction of bound complexes with a complex conformation specific antibody, and interpolating the temperature at which 50% of complexes are dissociated. A binding datum that specifies the temperature at which half of the binding partners are forming a complex and the other half are unbound. PERSON: Bjoern Peters, Randi Vita melting temperature (Tm) IEDB 50% dissociation of binding temperature (Tm) equilibrium dissociation constant (KD) approximated by IC50 A measurement of an IC50 value under specific assay conditions approximates KD, namely the binding reaction is at an equilibrium, there is a single population of sites on the receptor that competitor and ligand are binding to, and the concentration of the receptor must be much less than the KD for the competitor and the ligand. In this case, according to Cheng and Prussoff, KD = IC50 / (1 + Lstot / KDs), in which Lstot is the total concentration of the labeled competitor and KDs is the KD value of that competitor. PERSON: Bjoern Peters, Randi Vita http://dx.doi.org/10.1016/0006-2952(73)90196-2 equilibrium dissociation constant (KD) approximated by IC50 DNA sequence data The part of a FASTA file that contains the letters ACTGGGAA A sequence data item that is about the primary structure of DNA OBI call; Bjoern Peters OBI call; Melanie Courtout 8/29/11 call: This is added after a request from Melanie and Yu. They should review it further. This should be a child of 'sequence data', and as of the current definition will infer there. DNA sequence data assigning gene property based on phenotypic assessment Interpreting data from assays that evaluate the qualities or dispositions inhering in an organism or organism part and comparing it to data from other organisms that have a defined genetic difference, and assigning a property to the product of the targeted gene as a result. Philly workshop 2011 Philly workshop 2011 assigning gene property based on phenotypic assessment equilibrium dissociation constant (KD) approximated by EC50 A measurement of an EC50 value under specific assay conditions approximates KD, namely the binding reaction is at an equilibrium, and the concentration of the receptor must be much less than the KD for the ligand. PERSON: Bjoern Peters, Randi Vita Assay Development: Fundamentals and Practices, By Ge Wu, page 74 equilibrium dissociation constant (KD) approximated by EC50 half life of binding datum The 45 minute period in which one half of the complexes formed by peptide ligand bound to a HLA-A*0201molecule disassociate. A half life datum of the time it takes for 50% of bound complexes in an ensemble to disassociate in absence of re-association. PERSON: Bjoern Peters, Randi Vita IEDB half life of binding datum binding A peptide binding to an MHC molecule to form a complex. The process of material entities forming complexes. 9/28/11 BP: The disposition referenced is the one of the ligand to bind the molecule. This along with binding as a function / process needs to be figured out with GO which is inconsistent at this point. PERSON: Bjoern Peters, Randi Vita IEDB binding PDB file chain The 'D' chain in the PDB file 2BSE identifies the heavy chain of the antibody in the protein:antibody complex A 3D structural organization datum that is part of a PDB file and has a specific chain identifier that identifies the entire information on a subset of the material entities PERSON: Bjoern Peters, Dorjee Tamang, Jason Greenbaum IEDB PDB file chain binding off rate measurement datum (koff) A rate measurement datum of how quickly bound complexes disassociate PERSON: Bjoern Peters, Randi Vita IEDB binding off rate measurement datum (koff) binding on rate measurement datum (kon) A rate measurement datum of how quickly bound complexes form PERSON: Bjoern Peters, Randi Vita IEDB binding on rate measurement datum (kon) average depth of sequence coverage An average value of the depth of sequence coverage based both on external (e.g. Cot-based size estimates) and internal (average coverage in the assembly) measures of genome size. Person: Chris Stoeckert, Jie Zheng NIAID GSCID-BRC metadata working group Depth of Coverage - Average NIAID GSCID-BRC average depth of sequence coverage specimen collection time measurement datum A time measurement datum that is the measure of the time when the specimens are collected. Person: Chris Stoeckert, Jie Zheng collection date NIAID GSCID-BRC metadata working group Specimen Collection Date NIAID GSCID-BRC specimen collection time measurement datum latitude coordinate measurement datum A measurement datum that is the measure of the latitude coordinate of a site. Person: Chris Stoeckert, Jie Zheng latitude NIAID GSCID-BRC metadata working group Specimen Collection Location - Latitude NIAID GSCID-BRC latitude coordinate measurement datum longitude coordinate measurement datum A measurement datum that is the measure of the longitude coordinate of a site. Person: Chris Stoeckert, Jie Zheng longitude NIAID GSCID-BRC metadata working group Specimen Collection Location - Longitude NIAID GSCID-BRC longitude coordinate measurement datum drawing a conclusion Concluding that the length of the hypotenuse is equal to the square root of the sum of squares of the other two sides in a right-triangle. Concluding that a gene is upregulated in a tissue sample based on the band intensity in a western blot. Concluding that a patient has a infection based on measurement of an elevated body temperature and reported headache. Concluding that there were problems in an investigation because data from PCR and microarray are conflicting. A planned process in which new information is inferred from existing information. drawing a conclusion sequence assembly process A data transformation that assembles two or more individual sequence reads into contiguous sequences (i.e., contigs). PRS/AGB: changed to restrictions by adding 2 possible specified outputs (N50 and genome coverage) for sequence assembly. Alejandra Gonzalez-Beltran PERSON: Jie Zheng, Chris Stoeckert Philippe Rocca-Serra NIAID GSCID-BRC metadata working group NIAID GSCID-BRC sequence assembly process number of errors Gigascience. 2012 Dec 27;1(1):18. doi: 10.1186/2047-217X-1-18. PMID: 23587118. see table2 a data item that is the number of times that a given process failed, as an integer Alejandra Gonzalez-Beltran Philippe Rocca-Serra PRS, AGB number of errors random access memory size Gigascience. 2012 Dec 27;1(1):18. doi: 10.1186/2047-217X-1-18. PMID: 23587118. "However, the error correction module in SOAPdenovo was designed for short Illumina reads (35-50 bp), which consumes an excessive amount of computational time and memory on longer reads, for example, over 150 GB memory running for two days using 40-fold 100 bp paired-end Illumina HiSeq 2000 reads" random access memory size is a scalar measurement datum which denotes the amount of physical memory know as random access memory present of a computer or required by a computational process or data transformation Alejandra Gonzalez-Beltran Philippe Rocca-Serra PRS, AGB random access memory size random access memory Random-access memory (RAM) is a form of computer data storage. A random-access device allows stored data to be accessed directly in any random order. In contrast, other data storage media such as hard disks, CDs, DVDs and magnetic tape, as well as early primary memory types such as drum memory, read and write data only in a predetermined order, consecutively, because of mechanical design limitations. Therefore, the time to access a given data location varies significantly depending on its physical location Alejandra Gonzalez-Beltran Philippe Rocca-Serra RAM http://en.wikipedia.org/wiki/RAM last accessed: 2013-12-02 random access memory testable hypothesis that fucoidan has a small statistically significant effect on AT3 level but no useful clinical effect as in-vivo anticoagulant, a paraphrase of part of the last paragraph of the discussion section of the paper 'Pilot clinical study to evaluate the anticoagulant activity of fucoidan', by Lowenthal et. al.PMID:19696660 An information content entity that expresses an assertion that is intended to be tested. In the Philly 2013 workshop, we recognized the limitations of "hypothesis textual entity", and we introduced this as more general. The need for the 'textual entity' term going forward is up for future debate. Group:2013 Philly Workshop group hypothesis Group:2013 Philly Workshop group testable hypothesis conclusion based on data The conclusion that a gene is upregulated in a tissue sample based on the band intensity in a western blot. The conclusion that a patient has a infection based on measurement of an elevated body temperature and reported headache. The conclusion that there were problems in an investigation because data from PCR and microarray are conflicting. The following are NOT conclusions based on data: data themselves; results from pure mathematics, e.g. "13 is prime". An information content entity that is inferred from data. In the Philly 2013 workshop, we recognized the limitations of "conclusion textual entity", and we introduced this as more general. The need for the 'textual entity' term going forward is up for future debate. Group:2013 Philly Workshop group Group:2013 Philly Workshop group conclusion based on data computation run time Gigascience. 2012 Dec 27;1(1):18. doi: 10.1186/2047-217X-1-18. PMID: 23587118. See Table 4 computation run time is a time measurement datum which corresponds the time expressed in second, minute, hour necessary for a computer program to complete a process execution, for example genome assembly. It is an important metrics as it indicates the resource occupancy and computer program efficiency. Alejandra Gonzalez-Beltran Philippe Rocca-Serra computation run time datum PRS,AGB computation run time categorical value specification A value specification that is specifies one category out of a fixed number of nominal categories PERSON:Bjoern Peters categorical value specification 1 1 scalar value specification A value specification that consists of two parts: a numeral and a unit label PERSON:Bjoern Peters scalar value specification value specification The value of 'positive' in a classification scheme of "positive or negative"; the value of '20g' on the quantitative scale of mass. An information content entity that specifies a value within a classification scheme or on a quantitative scale. This term is currently a descendant of 'information content entity', which requires that it 'is about' something. A value specification of '20g' for a measurement data item of the mass of a particular mouse 'is about' the mass of that mouse. However there are cases where a value specification is not clearly about any particular. In the future we may change 'value specification' to remove the 'is about' requirement. PERSON:Bjoern Peters value specification genome coverage Gigascience. 2012 Dec 27;1(1):18. doi: 10.1186/2047-217X-1-18. PMID: 23587118. "The genome coverage increased from 81.16% to 93.91%" A data item that is the total number of bases in reads, divided by genome size, assumed to be the reference size (for instance of 3.10 Gb for human and 2.73 Gb for mouse) and refers to the percentage of the genome that is contained in the assembly based on size estimates; these are usually based on cytological techniques. Genome coverage of 90–95% is generally considered to be good, as most genomes contain a considerable fraction of repetitive regions that are difficult to sequence. So it is not a cause for concern if the genome coverage of an assembly is a bit less than 100%. Alejandra Gonzalez-Beltran Philippe Rocca-Serra A beginner's guide to eukaryotic genome annotation. Yandell M, Ence D. Nat Rev Genet. 2012 Apr 18;13(5):329-42. doi: 10.1038/nrg3174. PMID: 22510764 genome coverage N50 Gigascience. 2012 Dec 27;1(1):18. doi: 10.1186/2047-217X-1-18. PMID: 23587118. "Here, the contig and scaffold N50 of the YH genome were ~20.9 kbp and ~22 Mbp" the weighted median item size or N50 is a weighted median of the lengths of items, equal to the length of the longest item i such that the sum of the lengths of items greater than or equal in length to i is greater than or equal to half the length of all of the items. With regard to assemblies the items are typically contigs or scaffolds. It therefore denotes the ability of the software to create contigs and provides information about the resulting sequence assembly Alejandra Gonzalez-Beltran Philippe Rocca-Serra weighted median item size adapted from: "http://genome.cshlp.org/content/21/12/2224.full?sid=74019122-f944-4ccc-bffe-d16fdd0e7d6c" (from table 7) and from "http://www.nature.com/nrg/journal/v14/n3/full/nrg3367.html" N50 contig N50 Gigascience. 2012 Dec 27;1(1):18. doi: 10.1186/2047-217X-1-18. PMID: 23587118. "Here, the contig and scaffold N50 of the YH genome were ~20.9 kbp and ~22 Mbp" N50 statistic computed for the contigs produced by the assembly process. A contig N50 is calculated by first ordering every contig by length from longest to shortest. Next, starting from the longest contig, the lengths of each contig are summed, until this running sum equals one-half of the total length of all contigs in the assembly. The contig N50 of the assembly is the length of the shortest contig in this list. Alejandra Gonzalez-Beltran Philippe Rocca-Serra adapted from: nature:http://www.nature.com/nrg/journal/v13/n5/box/nrg3174_BX1.html contig N50 scaffold N50 Gigascience. 2012 Dec 27;1(1):18. doi: 10.1186/2047-217X-1-18. PMID: 23587118. "Here, the contig and scaffold N50 of the YH genome were ~20.9 kbp and ~22 Mbp" N50 statistic computed for the scaffold produced by the assembly process. The method for computing the value is similar to that of contig N50 but uses scaffold information instead of contig information Alejandra Gonzalez-Beltran Philippe Rocca-Serra adapted from: nature:http://www.nature.com/nrg/journal/v13/n5/box/nrg3174_BX1.html scaffold N50 sequencing library multiplexing http://www.illumina.com/technology/multiplexing_sequencing_assay.ilmn a planned process which consists in running a set of samples as a pool in one single instrument run of data acquisition process while retaining the ability to associate individual results to each of the individual input samples thanks to the use of a multiplex identifier, introduced during the ligation step of the individual library preparation and specific to a given sample. PERSON:Philippe Rocca-Serra OBI sequencing library multiplexing sequence library deconvolution is a data transformation which uses sequence alignment and 'multiplex identifier sequence' information to pull together all reads belonging to a given single sample following the sequencing of a multiplexed library which combining several samples in one sequencing event PERSON: Philippe Rocca-Serra PRS for OBI sequence library deconvolution multiplexing sequence identifier We designed primers specifically to amplify protease and reverse transcriptase from Brazilian HIV subtypes and developed a multiplexing scheme using multiplex identifier tags to minimize cost while providing more robust data than traditional genotyping techniques. in http://www.ncbi.nlm.nih.gov/pubmed/22574170 A multiplexing sequence identifier is a nucleic acid sequence which is used in a ligation step of library preparation process to allow pooling of samples while maintaining ability to identify individual source material and creation of a multiplexed library PERSON:Philippe Rocca-Serra OBI multiplexing sequence identifier operational taxonomic unit matrix http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1610290/ Operational Taxonomic Unit matrix is a data item, organized as a table, where organismal taxonomic units, computed by sequence analysis and genetic distance calculation, are counted in a set of biological or environmental samples. The table is used to appraise biodiversity of a population or community of living organism. PERSON:Philippe Rocca-Serra PRS for OBI operational taxonomic unit matrix multiplexed sequencing library http://www.ncbi.nlm.nih.gov/pubmed/24997861 Nat Methods. 2014 Aug;11(8):834-40. doi: 10.1038/nmeth.3022. Epub 2014 Jul 6. Accelerated chromatin biochemistry using DNA-barcoded nucleosome libraries. a multiplexed library is a material entity which is the output of a library preparation process that uses a ligation step to attach a unique multiplexing sequence identifier to a specific sample, then mixes several such tagged samples prior to the library amplification process proper. A multiplexed library allows the sequencing of several samples in one sequencing run. PERSON:Philippe Rocca-Serra DNA-barcoded sequencing library PRS for OBI multiplexed sequencing library organism animal fungus plant virus A material entity that is an individual living system, such as animal, plant, bacteria or virus, that is capable of replicating or reproducing, growth and maintenance in the right environment. An organism may be unicellular or made up, like humans, of many billions of cells divided into specialized tissues and organs. 10/21/09: This is a placeholder term, that should ideally be imported from the NCBI taxonomy, but the high level hierarchy there does not suit our needs (includes plasmids and 'other organisms') 13-02-2009: OBI doesn't take position as to when an organism starts or ends being an organism - e.g. sperm, foetus. This issue is outside the scope of OBI. GROUP: OBI Biomaterial Branch WEB: http://en.wikipedia.org/wiki/Organism organism specimen Biobanking of blood taken and stored in a freezer for potential future investigations stores specimen. A material entity that has the specimen role. Note: definition is in specimen creation objective which is defined as an objective to obtain and store a material entity for potential use as an input during an investigation. PERSON: James Malone PERSON: Philippe Rocca-Serra GROUP: OBI Biomaterial Branch specimen data transformation The application of a clustering protocol to microarray data or the application of a statistical testing method on a primary data set to determine a p-value. A planned process that produces output data from input data. Elisabetta Manduchi Helen Parkinson James Malone Melanie Courtot Philippe Rocca-Serra Richard Scheuermann Ryan Brinkman Tina Hernandez-Boussard data analysis data operation data processing Branch editors data transformation logistic-log curve fitting Typically used in an enzyme-linked immunosorbent assay (ELISA) to model the relationship between optical density (OD) and dilution. In this case a and d correspond to the theoretical OD of the assay at zero and infinite concentrations, respectively; c is the dilution associated with the point of symmetry of the sigmoid and is located at the midpoint of the assay found at the inflection point of the curve; b is a curvature parameter and is related to the slope of the curve. A logistic-log curve fitting is a curve fitting where a curve of the form y=d+((a-d)/(1+(x/c)^b)) is obtained, where a, b, c, and d are determined so to optimize its fit to the input data points (x_1, y_1), (x_2, y_2), ..., (x_n, y_n). Elisabetta Manduchi James Malone Melanie Courtot Ryan Brinkman ARTICLE: Plikaytis B.D. et al. (1991), J. Clin. Microbiol. 29(7): 1439-1448 logistic-log curve fitting logit-log curve fitting Typically used in an enzyme-linked immunosorbent assay (ELISA) to model the relationship between optical density (OD) and dilution. In this case OD_0 (also referred to OD_min) and OD_infty (also referred to OD_max) correspond to the theoretical OD of the assay at zero and infinite concentrations, respectively. A logit-log curve fitting is a curve fitting where first the limits y_0 an y_infty of y when x->0 and x->infinity, respectively, are estimated from the input data points (x_1, y_1), (x_2,y_2), ..., (x_n, y_n). Then a curve with equation log((y-y_0)/(y_infty-y))=a+b log(x) is obtained, where a and b are determined to optimize its fit to the input data points. The above definition refers to the 'fully specified' logit-log model. The reduced form of this, when it is assumed that y_0=0, is named 'partially specified' logit-log model. Elisabetta Manduchi James Malone Melanie Courtot Ryan Brinkman ARTICLE: Plikaytis B.D. et al. (1991), J. Clin. Microbiol. 29(7): 1439-1448 logit-log curve fitting log-log curve fitting Typically used in an enzyme-linked immunosorbent assay (ELISA) to model the relationship between optical density (OD) and dilution. A log-log curve fitting is a curve fitting where first a logarithmic transformation is applied both to the x and the y coordinates of the input data points (x_1, y_1), (x_2, y_2), ..., (x_n, y_n), and then coefficients a and b are determined to optimize the fit of log(y)=a+b*log(x) to these input data points. Elisabetta Manduchi James Malone Melanie Courtot Ryan Brinkman ARTICLE: Plikaytis B.D. et al. (1991), J. Clin. Microbiol. 29(7): 1439-1446 log-log curve fitting feature extraction objective A feature extraction objective is a data transformation objective where the aim of the data transformation is to generate quantified values from a scanned image. Elisabetta Manduchi James Malone TERM: http://mged.sourceforge.net/ontologies/MGEDOntology.owl#feature_extraction feature extraction objective biexponential transformation This type of transformation is typically used in flow cytometry. A biexponential transformation is a data transformation that, for each (one dimensional) real number input x, outputs an approximation (found, e.g. with the Newton's method) to a solution y of the equation B(y)-x=0, where B denotes a b transformation. Elisabetta Manduchi Joseph Spliden Ryan Brinkman WEB: http://flowcyt.sourceforge.net/gating/latest.pdf biexponential transformation box-cox transformation A box-cox transformation is a data transformation according to the methods of Box and Cox as described in the article Box, G. E. P. and Cox, D.R. (1964) An analysis of transformations. Journal of Royal Statistical Society, Series B, vol. 26, pp. 211-246. Ryan Brinkman ARTICLE: Box, G. E. P. and Cox, D.R. (1964), "An analysis of transformations", Journal of Royal Statistical Society, Series B, vol. 26, pp. 211-246. box-cox transformation hyperlog transformation This type of transformation is typically used in flow cytometry A hyperlog transformation ia a data transformation that, for each (one dimensional) real number input x, outputs an approximation (found, e.g. with the Newton's method) to a solution y of the equation EH(y)-x=0, where EH denotes an eh transformation. Elisabetta Manduchi Joseph Spliden Ryan Brinkman ARTICLE: Bagwell C.B. (2006), "Hyperlog - a flexible log-like transform for negative, zero, and positive valued data", Cytometry A 64, 34-42." http://flowcyt.sourceforge.net/gating/latest.pdf hyperlog transformation loess scale group transformation one-channel Loess scale group normalization applied to data from two one-channel expression microarray assays. A loess scale group transformation one-channel is a loess scale group transformation consisting in the application of a scale adjustment following a loess group transformation one-channel, to render the M group variances similar. Elisabetta Manduchi OTHER: Editor's adjustment based on MGED Ontology term loess scale group transformation one-channel logical transformation This type of transformation is typically used in flow cytometry. A logical transformation is a data transformation that, for each (one dimensional) real number input x, outputs an approximation (found, e.g. with the Newton's method) to a solution y of the equation S(y)-x=0, where S denotes an s transformation. Elisabetta Manduchi Joseph Spliden Ryan Brinkman WEB: http://flowcyt.sourceforge.net/gating/latest.pdf logical transformation loess scale group transformation two-channel Loess scale group normalization applied to data from a two-channel expression microarray assay. A loess scale group transformation two-channel is a loess scale group transformation consisting in the application of a scale adjustment following a loess group transformation two-channel, to render the M group variances similar. Elisabetta Manduchi OTHER: Adjusted from MGED Ontology loess scale group transformation two-channel loess global transformation one-channel Loess global normalization applied to data from two one-channel expression microarray assays, where the curve is obtained using all reporters. The goal is to remove intensity-dependent biases. A loess global transformation one-channel is a loess global transformation in the special case where the input is the result of an MA transformation applied to intensities from two related one-channel assays. Elisabetta Manduchi OTHER: Editor's generalization based on MGED Ontology term loess global transformation one-channel split-scale transformation This type of transformation is typically used in flow cytometry A split-scale transformation is a data transformation which is an application of a function f described as follows to a (one dimensional) real number input. f(x)=a*x+b if x=for x>t; where log denotes a logarithmic transformation and a, b, c, d, r, t are real constants, with a, c, d, r, t positive, chosen so that f is continuous with a continuous derivative at the transition point t. Elisabetta Manduchi Joseph Spliden Ryan Brinkman WEB: http://flowcyt.sourceforge.net/gating/latest.pdf split-scale transformation loess global transformation two-channel Loess global normalization applied to data from a two-channel expression microarray assay, where the curve is obtained using all reporters. The goal is to remove intensity-dependent biases. A loess global transformation two-channel is a loess global transformation in the special case where the input the result of an MA transformation applied to intensities from the two channels of a two-channel assay. Elisabetta Manduchi OTHER: Editor's generalization based on MGED Ontology term loess global transformation two-channel sine transformation sine(0)=0, sine(pi/2)=1, sine(pi)=0, sine(3*pi/2)=-1, sine(pi/6)=1/2, sine(x+2*k*pi)=sine(x) where k is any integer, etc. A sine transformation is a data transformation which consists in applying the sine function to a (one dimensional) real number input. The sine function is one of the basic trigonometric functions and a definition is provided, e.g., at http://mathworld.wolfram.com/Sine.html. Elisabetta Manduchi WEB: http://mathworld.wolfram.com/Sine.html sine transformation cosine transformation cosine(0)=1, cosine(pi/2)=0, cosine(pi)=-1, cosine(3*pi/2)=0, cosine(pi/3)=1/2, cosine(x+2*k*pi)=cosine(x) where k is any integer, etc. A cosine transformation is a data transformation which consists in applying the cosine function to a (one dimensional) real number input. The cosine function is one of the basic trigonometric functions and a definition is provided, e.g., at http://mathworld.wolfram.com/Cosine.html. Elisabetta Manduchi Philippe Rocca-Serra WEB: http://mathworld.wolfram.com/Cosine.html cosine transformation loess group transformation one-channel A loess group transformation one-channel is a loess group transformation in the special case where the input is the result of an MA transformation applied to intensities from two related one-channel assays. A loess group transformation one-channel is a loess group transformation in the special case where the input is the result of an MA transformation applied to intensities from two related one-channel assays. Elisabetta Manduchi OTHER: Editor's generalization based on MGED Ontology term loess group transformation one-channel loess group transformation two-channel A loess group transformation two-channel is a loess group transformation in the special case where the input is the result of an MA transformation applied to intensities from the two channels of a two-channel assay. A loess group transformation two-channel is a loess group transformation in the special case where the input is the result of an MA transformation applied to intensities from the two channels of a two-channel assay. Elisabetta Manduchi OTHER: Editor's generalization based on MGED Ontology term loess group transformation two-channel homogeneous polynomial transformation a*x, with a non-zero, is a homogeneous polynomial of degree 1 in 1 variable, a*x^2, with a non-zero, is a homogeneous polynomial of degree 2 in 1 variable; a_1*x_1+...+a_n*x_n, with at least one of the a_i's non-zero, is a homogeneous polynomial of degree one in n variables; a*x_n^3+b*x_1*x_2*x_3, with at least one of a and b non-zero, is a homogeneous polynomial of degree 3 in n variables. A homogeneous polynomial transformation is a polynomial transformation where all the term of the polynomial have the same degree. Elisabetta Manduchi WEB: http://mathworld.wolfram.com/HomogeneousPolynomial.html homogeneous polynomial transformation linlog transformation This can be used for microarray normalization, e.g. to normalize the data from a two-channel expression microarray assay, as described in PMID 16646782. A linlog transformation is a data transformation, described in PMID 16646782, whose input is a matrix [y_ik] and whose output is a matrix obtained by applying formula (9) of this paper, where values below an appropriately determined threshold (dependent on the row i) are transformed via a polynomial of degree 1, and values above this threshold are transformed via a logarithm. Elisabetta Manduchi Philippe Rocca-Serra PMID: 16646782 linlog transformation variance stabilizing transformation This can be used for expression microarray assay normalization and it is referred to as "variance stabilizing normalization", according to the procedure described e.g. in PMID 12169536. A variance stabilizing transformation is a data transformation, described in PMID 12169536, whose input is a matrix [y_ik] and whose output is a matrix obtained by applying formula (6) in this paper. One of the goals is to obtain an output matrix whose rows have equal variances. The method relies on various assumptions described in the paper. Elisabetta Manduchi James Malone Melanie Courtot variance stabilising transformation PMID: 12169536 variance stabilizing transformation loess global transformation A loess global transformation is a loess transformation where only one loess fitting is performed, utilizing one subset of (or possibly all of) the data points in the input so that there is only one resulting loess curve y=f(x) which is used for the transformation. Elisabetta Manduchi James Malone Melanie Courtot Philippe Rocca-Serra OTHER: Editor's generalization based on MGED Ontology term loess global transformation loess group transformation A loess group transformation is a loess transformation where the input is partitioned into groups and for each group a loess fitting is performed, utilizing a subset of (or possibly all of) the data points in that group. Thus, a collection of loess curves y=f_i(x) is generated, one per group. Each (x, y) in the input is transformed into (x, y-f_i(x)), where f_i(x) is the curve corresponding to the group to which that data point belongs. Elisabetta Manduchi James Malone Melanie Courtot Philippe Rocca-Serra OTHER: Editor's generalization based on MGED Ontology term loess group transformation loess scale group transformation A loess scale group transformation is a data transformation consisting in the application of a scale adjustment following a loess group transformation, to render the group variances for the second variable (y) similar. Has objective scaling. Elisabetta Manduchi James Malone Melanie Courtot OTHER: Editor's generalization based on MGED Ontology term loess scale group transformation total intensity transformation single This can be used as a simple normalization method for expression microarray assays. For example, each intensity from a one-channel microarray assay is multiplied by a constant so that the output mean intensity over the microarray equals a desired target T (the multiplicative constant in this case is the T/(mean intensity)). A total intensity transformation single is a data transformation that takes as input an n-dimensional (real) vector and multiplies each component of this vector by a coefficient, where the coefficient is obtained by taking the sum of the input components or of a subset of these, multiplied by a constant of choice. Elisabetta Manduchi Helen Parkinson James Malone Melanie Courtot Philippe Rocca-Serra OTHER: Adjusted from MGED Ontology Note that if the word "sum" is replaced by the word "mean" in the definition, the resulting definition is equivalent. total intensity transformation single total intensity transformation paired This can be used as a simple normalization method for the two channels from a two-channel expression microarray assay or from two related one-channel expression microarray assays. A total intensity transformation paired is a data transformation that takes as input two n-dimensional (real) vectors and multiplies each component of the first vector by a coefficient, where the coefficient is obtained by taking the ratio of the sum of the second input components or of a subset of these by the sum of the first input components or of a subset of these (the same subset is used for the two vectors). Elisabetta Manduchi Philippe Rocca-Serra OTHER: Adjusted from MGED Ontology Note that if the word "sum" is replaced by the word "mean" in the definition, the resulting definition is equivalent. total intensity transformation paired quantile transformation This can be used for expression microarray assay normalization and it is referred to as "quantile normalization", according to the procedure described e.g. in PMID 12538238. A quantile transformation is a data transformation that takes as input a collection of data sets, where each can be thought as an n-dimensional (real) vector, and which transforms each data set so that the resulting output data sets have equal quantiles. Elisabetta Manduchi PERSON: Elisabetta Manduchi quantile transformation mean centering This can be used as a normalization method in expression microarray assays. For example, given a two-channel microarray assay, the log ratios of the two channels (M values) can be mean-centered. A mean centering is a data transformation that takes as input an n-dimensional (real) vector, performs a mean calculation on its components, and subtracts the resulting mean from each component of the input. Elisabetta Manduchi Philippe Rocca-Serra mean centring PERSON: Elisabetta Manduchi mean centering median centering This can be used as a normalization method in expression microarray assays. For example, given a two-channel microarray assay, the log ratios of the two channels (M values) can be median-centered. A median centering is a data transformation that takes as input an n-dimensional (real) vector, performs a median calculation on its components, and subtracts the resulting median from each component of the input. Elisabetta Manduchi Philippe Rocca-Serra median centring PERSON: Elisabetta Manduchi median centering differential expression analysis objective Analyses implemented by the SAM (http://www-stat.stanford.edu/~tibs/SAM), PaGE (www.cbil.upenn.edu/PaGE) or GSEA (www.broad.mit.edu/gsea/) algorithms and software A differential expression analysis objective is a data transformation objective whose input consists of expression levels of entities (such as transcripts or proteins), or of sets of such expression levels, under two or more conditions and whose output reflects which of these are likely to have different expression across such conditions. Elisabetta Manduchi PERSON: Elisabetta Manduchi differential expression analysis objective K-fold cross validation method K-fold cross-validation randomly partitions the original sample into K subsamples. Of the K subsamples, a single subsample is retained as the validation data for testing the model, and the remaining K - 1 subsamples are used as training data. The cross-validation process is then repeated K times (the folds), with each of the K subsamples used exactly once as the validation data. The K results from the folds then can be averaged (or otherwise combined) to produce a single estimation. The advantage of this method over repeated random sub-sampling is that all observations are used for both training and validation, and each observation is used for validation exactly once. 10-fold cross-validation is commonly used Person:Helen Parkinson Tina Boussard K-fold cross validation method leave one out cross validation method The authors conducted leave-one-out cross validation to estimate the strength and accuracy of the differentially expressed filtered genes. http://bioinformatics.oxfordjournals.org/cgi/content/abstract/19/3/368 is a data transformation : leave-one-out cross-validation (LOOCV) involves using a single observation from the original sample as the validation data, and the remaining observations as the training data. This is repeated such that each observation in the sample is used once as the validation data 2009-11-10. Tracker: https://sourceforge.net/tracker/?func=detail&aid=2893049&group_id=177891&atid=886178 Person:Helen Parkinson leave one out cross validation method jackknifing method simple weighting procedure is suggested for combining information over alleles and loci, and sample variances may be estimated by a jackknife procedure Jacknifing is a re-sampling data transformation process used to estimate the precision of sampling statistics and is a resampling method Helen Parkinson jackknifing http://en.wikipedia.org/wiki/Resampling_%28statistics%29 jackknifing method boostrapping Although widely accepted that high throughput biological data are typically highly noisy, the effects that this uncertainty has upon the conclusions we draw from these data are often overlooked. However, in order to assign any degree of confidence to our conclusions, we must quantify these effects. Bootstrap resampling is one method by which this may be achieved. Bootstrapping is a statistical method for estimating the sampling distribution of a statistic by sampling with replacement from the original data, most often with the purpose of deriving robust estimates of standard errors and confidence intervals of a population parameter like a mean, median, proportion, odds ratio, correlation coefficient or regression coefficient Helen Parkinson Bootstrapping is a data transformation process which estimates the precision of sampling statistics by drawing randomly with replacement from a set of data points boostrapping Benjamini and Hochberg false discovery rate correction method Statistical significance of the 8 most represented biological processes (GO level 4) among E7 6 month upregulated genes following analysis with DAVID software; Benjamini-Hochberg FDR (false discovery rate) A data transformation process in which the Benjamini and Hochberg method sequential p-value procedure is applied with the aim of correcting false discovery rate 2011-03-31: [PRS]. specified input and output of dt which were missing Helen Parkinson Philippe Rocca-Serra Helen Parkinson Benjamini and Hochberg false discovery rate correction method pareto scaling A pareto scaling is a data transformation that divides all measurements of a variable by the square root of the standard deviation of that variable. Elisabetta Manduchi Philippe Rocca-Serra PMID:16762068 pareto scaling modular decomposition Molecular decomposition is the partition of a network into distinct subgraphs for the purpose of identifying functional clusters. The network data is run through any of several existing algorithms designed to partition a network into distinct subgraphs for the purpose of isolating groups of functionally linked biological elements such as proteins. Tina Hernandez-Boussard editor modular decomposition k-means clustering A k-means clustering is a data transformation which achieves a class discovery or partitioning objective, which takes as input a collection of objects (represented as points in multidimensional space) and which partitions them into a specified number k of clusters. The algorithm attempts to find the centers of natural clusters in the data. The most common form of the algorithm starts by partitioning the input points into k initial sets, either at random or using some heuristic data. It then calculates the mean point, or centroid, of each set. It constructs a new partition by associating each point with the closest centroid. Then the centroids are recalculated for the new clusters, and the algorithm repeated by alternate applications of these two steps until convergence, which is obtained when the points no longer switch clusters (or alternatively centroids are no longer changed). Elisabetta Manduchi James Malone Philippe Rocca-Serra WEB: http://en.wikipedia.org/wiki/K-means k-means clustering hierarchical clustering A hierarchical clustering is a data transformation which achieves a class discovery objective, which takes as input data item and builds a hierarchy of clusters. The traditional representation of this hierarchy is a tree (visualized by a dendrogram), with the individual input objects at one end (leaves) and a single cluster containing every object at the other (root). James Malone WEB: http://en.wikipedia.org/wiki/Data_clustering#Hierarchical_clustering hierarchical clustering average linkage hierarchical clustering An average linkage hierarchical clustering is an agglomerative hierarchical clustering which generates successive clusters based on a distance measure, where the distance between two clusters is calculated as the average distance between objects from the first cluster and objects from the second cluster. Elisabetta Manduchi PERSON: Elisabetta Manduchi average linkage hierarchical clustering complete linkage hierarchical clustering an agglomerative hierarchical clustering which generates successive clusters based on a distance measure, where the distance between two clusters is calculated as the maximum distance between objects from the first cluster and objects from the second cluster. Elisabetta Manduchi PERSON: Elisabetta Manduchi complete linkage hierarchical clustering single linkage hierarchical clustering A single linkage hierarchical clustering is an agglomerative hierarchical clustering which generates successive clusters based on a distance measure, where the distance between two clusters is calculated as the minimum distance between objects from the first cluster and objects from the second cluster. Elisabetta Manduchi PERSON: Elisabetta Manduchi single linkage hierarchical clustering Benjamini and Yekutieli false discovery rate correction method The expression set was compared univariately between the stroke patients and controls, gene list was generated using False Discovery Rate correction (Benjamini and Yekutieli) A data transformation in which the Benjamini and Yekutieli method is applied with the aim of correcting false discovery rate 2011-03-31: [PRS]. specified input and output of dt which were missing Helen Parkinson Philippe Rocca-Serra Helen Parkinson Benjamini and Yekutieli false discovery rate correction method dimensionality reduction A dimensionality reduction is data partitioning which transforms each input m-dimensional vector (x_1, x_2, ..., x_m) into an output n-dimensional vector (y_1, y_2, ..., y_n), where n is smaller than m. Elisabetta Manduchi James Malone Melanie Courtot Philippe Rocca-Serra data projection PERSON: Elisabetta Manduchi PERSON: James Malone PERSON: Melanie Courtot dimensionality reduction principal components analysis dimensionality reduction A principal components analysis dimensionality reduction is a dimensionality reduction achieved by applying principal components analysis and by keeping low-order principal components and excluding higher-order ones. Elisabetta Manduchi James Malone Melanie Courtot Philippe Rocca-Serra pca data reduction PERSON: Elisabetta Manduchi PERSON: James Malone PERSON: Melanie Courtot principal components analysis dimensionality reduction probabilistic algorithm A probabilistic algorithm is one which involves an element of probability or randomness in the transformation of the data. James Malone PERSON: James Malone probabilistic algorithm expectation maximization EM is a probabilistic algorithm used to estimate the maximum likelihood of parameters from existing data where the model involves unobserved latent variables. The input to this method is the data model for which the estimation is performed over and the output is an approximated probability function. James Malone PERSON: James Malone expectation maximization global modularity calculation A network graph quality calculation in which an input data set of subgraph modules and their in-degree and out-degree qualities is used to calculate the average modularity of subgraphs within the network. Richard Scheuermann PERSON: Richard Scheuermann global modularity calculation dye swap merge A dye swap merge is a replicate analysis which takes as input data from paired two-channel microarray assays where the sample labeled with one dye in the first assay is labeled with the other dye in the second assay and vice versa. The output for each reporter is obtained by combining its (raw or possibly pre-processed) M values in the two assays, where the M value in an assay is defined as the difference of the log intensities in the two channels. This can be used as a normalization step, when appropriate assumptions are met. Elisabetta Manduchi James Malone PERSON: Elisabetta Manduchi PERSON: James Malone dye swap merge moving average The moving average is often used to handle data from tiling arrays. A moving average is a data transformation in which center calculations, usually mean calculations, are performed on values within a sliding window across the input data set. Elisabetta Manduchi Helen Parkinson Philippe Rocca-Serra PERSON: Elisabetta Manduchi PERSON: Helen Parkinson moving average replicate analysis Replicate analysis can be used in microarray analysis to identify and potentially exclude low quality data. A replicate analysis is a data transformation in which data from replicates are combined, e.g. through descriptive statistics calculations, and the results might be utilized for a variety of purposes, like assessing reproducibility, identifying outliers, normalizing, etc. Elisabetta Manduchi Helen Parkinson PERSON: Helen Parkinson PERSON:Elisabetta Manduchi replicate analysis b cell epitope prediction A B cell epitope prediction takes as input an antigen sequence, and through an analysis of this sequence, produces as output a prediction of the likelihood the biomaterial is a B Cell Epitope. Helen Parkinson PERSON: Helen Parkinson b cell epitope prediction mhc binding prediction An MHC binding prediction takes an input of a biomaterial sequence and through an analysis of this sequence, produces as output a prediction of the likelihood that the biomaterial will bind to an MHC molecule. Helen Parkinson PERSON: Helen Parkinson mhc binding prediction t cell epitope prediction A T cell epitope prediction takes as input an antigen sequence, and through an analysis of this sequence, produces as output a prediction of the likelihood the biomaterial is a T cell epitope. Helen Parkinson PERSON: Helen Parkinson t cell epitope prediction data imputation Imputation is a means of filling in missing data values from a predictive distribution of the missing values. The predictive distribution can be created either based on a formal statistical model (i,e, a multivariate normal distribution) or an algorithm. Monnie McGee ARTICLE: Little, RJA and Rubin, DB (2002). Statistical Analysis with Missing Data, Second Edition. John Wiley: Hoboken New Jersey, pp. 59-60. data imputation continuum mass spectrum A continuum mass spectrum is a data transformation that contains the full profile of the detected signals for a given ion. PERSON: James Malone PERSON: Tina Hernandez-Boussard PERSON: Tina Boussard continuum mass spectrum characteristic path length calculation Quantifying subgraph navigability based on shortest-path length averaged over all pairs of subgraph vertices PERSON: Tina Hernandez-Boussard PERSON: Tina Hernandez-Boussard characteristic path length calculation centroid mass spectrum A centroid mass spectrum is a data transformation in which many points are used to delineate a mass spectral peak, is converted into mass-centroided data by a data compression algorithm. The centroided mass peak is located at the weighted center of mass of the profile peak. The normalized area of the peak provides the mass intensity data. Person:Tina Hernandez-Boussard centroid mass spectrum calculation centroiding centroid mass spectrum centroid mass spectrum Holm-Bonferroni family-wise error rate correction method t-tests were used with the type I error adjusted for multiple comparisons, Holm's correction (HOLM 1979), and false discovery rate, http://www.genetics.org/cgi/content/full/172/2/1179 a data transformation that performs more than one hypothesis test simultaneously, a closed-test procedure, that controls the familywise error rate for all the k hypotheses at level ? in the strong sense. Objective: multiple testing correction 2011-03-14: [PRS]. Class Label has been changed to address the conflict with the definition Also added restriction to specify the output to be a FWER adjusted p-value The 'editor preferred term' should be removed Person:Helen Parkinson Philippe Rocca-Serra WEB: http://en.wikipedia.org/wiki/Holm%E2%80%93Bonferroni_method Holm-Bonferroni family-wise error rate correction method edge weighting Edge weighting is the substitution or transformation of edge length using numerical data. Data input include a symmetric adjacency matrix for a network and a second data set, for example a list of interactor pairs and a confidence score associated with the experimental detection of each pair's interaction. Each element in the adjacency matrix is transformed or replaced with the corresponding number in the second data set. Output data are a modified adjacency matrix reflecting the transformed state of the network. Tina Hernandez-Boussard editor was classified under algorithm class which is not acceptable super-class TO BE DEALT WITH STILL BY RICHARD. JAMES edge weighting loess transformation A loess transformation is a data transformation that takes as input a collection of real number pairs (x, y) and, after performing (one or more) loess fittings, utilizes the resulting curves to transform each (x, y) in the input into (x, y-f(x)) where f(x) is one of the fitted curves. Elisabetta Manduchi James Malone Melanie Courtot Philippe Rocca-Serra OTHER: Editor's generalization based on MGED Ontology term loess transformation curve fitting data transformation A curve fitting is a data transformation that has objective curve fitting and that consists of finding a curve which matches a series of data points and possibly other constraints. Elisabetta Manduchi James Malone Melanie Courtot WEB: http://en.wikipedia.org/wiki/Curve_fitting curve fitting data transformation family wise error rate correction method A family wise error rate correction method is a multiple testing procedure that controls the probability of at least one false positive. 2011-03-31: [PRS]. creating a defined class by specifying the necessary output of dt allows correct classification of FWER dt Monnie McGee Philippe Rocca-Serra FWER correction Dudoit, Sandrine and van der Laan, Mark J. (2008) Multiple Testing Procedures with Applications to Genomics. New York: Springer , p. 19 family wise error rate correction method submatrix extraction When presented with the data from an expression microarray experiment in the form of a matrix, whose rows correspond to genes and whose columns correspond to samples, if one filters some of the genes and/or some of the samples out, the resulting data set corresponds to a submatrix of the original set. A submatrix extraction is a projection whose input is a matrix and whose output is a matrix obtained by selecting certain rows and columns from the input. (Note that, if one represents the input matrix as a vector obtained by concatenating its rows, then extracting a submatrix is equivalent to projecting this vector into that composed by the entries belonging to the rows and columns of interest from the input matrix.) Note that this can be considered as a special case of projection if one represents the input matrix as a vector obtained by concatenating its rows. Then extracting a submatrix is equivalent to projecting this vector into the entries belonging to the rows and columns of interest from the input matrix. Elisabetta Manduchi James Malone Melanie Courtot WEB: http://en.wikipedia.org/wiki/Submatrix submatrix extraction row submatrix extraction When presented with the data from an expression microarray experiment in the form of a matrix, whose rows correspond to genes and whose columns correspond to samples, if one filters some of the genes out, the resulting data set corresponds to a row submatrix of the original set. A row submatrix extraction is a submatrix extraction where all the columns of the input matrix are retained and selection only occurs on the rows. Elisabetta Manduchi James Malone Melanie Courtot PERSON: Elisabetta Manduchi PERSON: James Malone PERSON: Melanie Courtot row submatrix extraction column submatrix extraction When presented with the data from an expression microarray experiment in the form of a matrix, whose rows correspond to genes and whose columns correspond to samples, if one filters some of the samples out, the resulting data set corresponds to a column submatrix of the original set. A column submatrix extraction is a submatrix extraction where all the rows of the input matrix are retained and selection only occurs on the columns. Elisabetta Manduchi James Malone Melanie Courtot PERSON: Elisabetta Manduchi PERSON: James Malone PERSON: Melanie Courtot column submatrix extraction gating Gating is a property-based vector selection with the objective of partitioning a data vector set into vector subsets based on dimension values of individual vectors (events), in which vectors represent individual physical particles (often cells) of a sample and dimension values represent light intensity qualities as measured by flow cytometry. James Malone Josef Spidlen Melanie Courtot Richard Scheuermann Ryan Brinkman PERSON: James Malone PERSON: Josef Spidlen PERSON: Richard Scheuermann PERSON: Ryan Brinkman PERSON:Melanie Courtot gating descriptive statistical calculation objective A descriptive statistical calculation objective is a data transformation objective which concerns any calculation intended to describe a feature of a data set, for example, its center or its variability. Elisabetta Manduchi James Malone Melanie Courtot Monnie McGee PERSON: Elisabetta Manduchi PERSON: James Malone PERSON: Melanie Courtot PERSON: Monnie McGee descriptive statistical calculation objective mean calculation A mean calculation is a descriptive statistics calculation in which the mean is calculated by taking the sum of all of the observations in a data set divided by the total number of observations. It gives a measure of the 'center of gravity' for the data set. It is also known as the first moment. James Malone Monnie McGee Philippe Rocca-Serra PERSON: James Malone PERSON: Monnie McGee From Monnie's file comments - need to add moment_calculation and center_calculation roles but they don't exist yet - (editor note added by James Jan 2008) mean calculation network analysis A data transformation that takes as input data that describes biological networks in terms of the node (a.k.a. vertex) and edge graph elements and their characteristics and generates as output properties of the constituent nodes and edges, the sub-graphs, and the entire network. Richard Scheuermann network topology analysis PERSON: Richard Scheuermann network analysis sequence analysis objective A sequence analysis objective is a data transformation objective which aims to analyse some ordered biological data for sequential patterns. James Malone PERSON: James Malone sequence analysis objective longitudinal data analysis Longitudinal analysis is a data transformation used to perform repeated observations of the same items over long periods of time. PERSON: James Malone PERSON: Tina Boussard correlation analysis longitudinal data analysis longitudinal data analysis survival analysis objective Kaplan meier data transformation A data transformation objective which has the data transformation aims to model time to event data (where events are e.g. death and or disease recurrence); the purpose of survival analysis is to model the underlying distribution of event times and to assess the dependence of the event time on other explanatory variables PERSON: James Malone PERSON: Tina Boussard survival analysis http://en.wikipedia.org/wiki/Survival_analysis survival analysis objective mass spectrometry analysis A data transformation which has the objective of spectrum analysis. mass spectrometry analysis spread calculation data transformation A spread calculation is a data transformation that has objective spread calculation. James Malone EDITOR spread calculation data transformation Kaplan Meier a nonparametric (actuarial) data transformation technique for estimating time-related events. It is a univariate analysis that estimates the probability of the proportion of subjects in remission at a particular time, starting from the initiation of active date (time zero), and takes into account those lost to follow-up or not yet in remission at end of study (censored) PERSON: James Malone PERSON: Tina Boussard http://en.wikipedia.org/wiki/Kaplan%E2%80%93Meier_estimator Kaplan Meier multiple testing correction method A multiple testing correction method is a hypothesis test performed simultaneously on M > 1 hypotheses. Multiple testing procedures produce a set of rejected hypotheses that is an estimate for the set of false null hypotheses while controlling for a suitably define Type I error rate Monnie McGee multiple testing procedure PAPER: Dudoit, Sandrine and van der Laan, Mark J. (2008) Multiple Testing Procedures with Applications to Genomics. New York: Springer , p. 9-10. multiple testing correction method inter-rater reliability objective A study was conducted to determine the inter-rater reliability of common clinical examination procedures proposed to identify patients with lumbar segmental instability. Examples include joint-probability of agreement, Cohen's kappa and the related Fleiss' kappa, inter-rater correlation, concordance correlation coefficient and intra-class correlation. a data transformation objective of determining the concordance or agreement between human judges. Person:Alan Ruttenberg Person:Helen Parkinson inter-rater agreement http://en.wikipedia.org/wiki/Inter-rater_reliability inter-rater reliability objective Westfall and Young family wise error rate correction Is a data transformation process in which the Westfall and Young method is applied with the aim of controlling for multiple testing 2011-03-31: [PRS]. specified input and output of dt which were missing PRS: 2011-03-31: set specified input and specified output to the data transformation Helen Parkinson Westfall and Young FWER correction Westfall and Young family wise error rate correction polynomial transformation a*x+b, with a non-zero, is a polynomial of degree one in one variable; a*x^2+b*x+c, with a nonzero, is a polynomial of degree 2 in 1 variable; a*x*y+b*y+c, with a non-zero, is a polynomial of degree 2 in 2 variables (x and y); a_1*x_1+...+a_n*x_n+b, with at least one of the a_i's non-zero, is a polynomial of degree one in n variables A polynomial transformation is a data transformation that is obtained through a polynomial, where a polynomial is a mathematical expression involving a sum of powers in one or more variables multiplied by coefficients (e.g. see http://mathworld.wolfram.com/Polynomial.html). The number of variables and the degree are properties of a polynomial. The degree of a polynomial is the highest power of its terms, where the terms of a polynomial are the individual summands with the coefficients omitted. Elisabetta Manduchi WEB: http://mathworld.wolfram.com/Polynomial.html polynomial transformation logarithmic transformation A logarithmic transformation is a data transformation consisting in the application of the logarithm function with a given base a (where a>0 and a is not equal to 1) to a (one dimensional) positive real number input. The logarithm function with base a can be defined as the inverse of the exponential function with the same base. See e.g. http://en.wikipedia.org/wiki/Logarithm. Elisabetta Manduchi WEB: http://en.wikipedia.org/wiki/Logarithm logarithmic transformation exponential transformation An exponential transformation is a data transformation consisting in the application of the exponential function with a given base a (where a>0 and a is typically not equal to 1) to a (one dimensional) real number input. For alternative definitions and properties of this function see, e.g., http://en.wikipedia.org/wiki/Exponential_function and http://en.wikipedia.org/wiki/Characterizations_of_the_exponential_function. Elisabetta Manduchi WEB: http://en.wikipedia.org/wiki/Characterizations_of_the_exponential_function WEB: http://en.wikipedia.org/wiki/Exponential_function exponential transformation non-negative matrix factorization Non-negative matrix factorization is used in text mining where document-term matrix is constructed with the weights of various terms (typically weighted word frequency information) from a set of documents. This matrix is factored into a term-feature and a feature-document matrix. Non negative matrix factorization is a data transformation in which factorises a matrix and which forces that all elements must be equal to or greater than zero. http://en.wikipedia.org/wiki/Non-negative_matrix_factorization non-negative matrix factorization soft independent modeling of class analogy analysis Soft independent modeling by class analogy (SIMCA) is a descriptive statistics method for supervised classification of data. The method requires a training data set consisting of samples (or objects) with a set of attributes and their class membership. The term soft refers to the fact the classifier can identify samples as belonging to multiple classes and not necessarily producing a classification of samples into non-overlapping classes. Tina Hernandez-Boussard SIMCA WEB: http://en.wikipedia.org/wiki/Soft_independent_modelling_of_class_analogies soft independent modeling of class analogy analysis discriminant function analysis Discriminant function analysis is a form of discriminant analysis used to determine which variables discriminate between two or more naturally occurring groups. Analysis is used to determine which variable(s) are the best predictors of a particular outcome. Tina Hernandez-Boussard WEB: http://www.statsoft.com/textbook/stdiscan.html discriminant function analysis canonical variate analysis canonical variate analysis is a form of discriminant analysis that takes several continuous predictor variables and uses the entire set to predict several criterion variables, each of which is also continuous. CVA simultaneously calculates a linear composite of all x variables and a linear composite of all y variables. Unlike other multivariate techniques, these weighted composites are derived in pairs. Each linear combination is called a canonical variate and takes the general linear form. Tina Hernandez-Boussard CVA WEB: http://en.wikipedia.org/wiki/Canonical_analysis canonical variate analysis linear discriminant functional analysis Linear discriminant functional analysis (LDFA) is a multivariate technique used in special applications where there are several intact groups (random assignment may be impossible) and they have been measured on several independent measures. Thus, you will want to describe how these groups differ on the basis of these measures. In this case, classification and prediction is the main objective. Tina Hernandez-Boussard PERSON: Tina Hernandez-Boussard linear discriminant functional analysis regression analysis method Regression analysis is a descriptive statistics technique that examines the relation of a dependent variable (response variable) to specified independent variables (explanatory variables). Regression analysis can be used as a descriptive method of data analysis (such as curve fitting) without relying on any assumptions about underlying processes generating the data. Tina Hernandez-Boussard BOOK: Richard A. Berk, Regression Analysis: A Constructive Critique, Sage Publications (2004) 978-0761929048 regression analysis method multiple linear regression analysis multiple linear regression is a regression method that models the relationship between a dependent variable Y, independent variables Xi, i = 1, ..., p, and a random term epsilon. The model can be written as Y = \beta_0 + \beta_1 X_1 + \beta_2 X_2 + \cdots +\beta_p X_p + \varepsilon where \beta_0 = 0 is the intercept ("constant" term), the \beta_i s are the respective parameters of independent variables, and p is the number of parameters to be estimated in the linear regression. Tina Hernandez-Boussard WEB:http://en.wikipedia.org/wiki/Linear_regression multiple linear regression analysis principal component regression The Principal Component Regression method is a regression analysis method that combines the Principal Component Analysis (PCA)spectral decomposition with an Inverse Least Squares (ILS) regression method to create a quantitative model for complex samples. Unlike quantitation methods based directly on Beer's Law which attempt to calculate the absorbtivity coefficients for the constituents of interest from a direct regression of the constituent concentrations onto the spectroscopic responses, the PCR method regresses the concentrations on the PCA scores. Tina Hernandez-Boussard WEB: : http://www.thermo.com/com/cda/resources/resources_detail/1,2166,13414,00.html principal component regression partial least square regression analysis Partial least squares regression is an extension of the multiple linear regression model (see, e.g., Multiple Regression or General Stepwise Regression). In its simplest form, a linear model specifies the (linear) relationship between a dependent (response) variable Y, and a set of predictor variables, the X's, so that Y = b0 + b1X1 + b2X2 + ... + bpXp In this equation b0 is the regression coefficient for the intercept and the bi values are the regression coefficients (for variables 1 through p) computed from the data. Tina Hernandez-Boussard PLS-RA ARTICLE: de Jong, S. (1993). SIMPLS: An alternative approach to partial least squares regression. Chemometrics and Intelligent Laboratory Systems, 18: 251-263. partial least square regression analysis discriminant analysis Discriminant function analysis is used to determine which variables discriminate between two or more naturally occurring groups. Analysis is used to determine which variable(s) are the best predictors of a particular outcome. Tina Hernandez-Boussard WEB: http://www.statsoft.com/textbook/stdiscan.html discriminant analysis partial least square discriminant analysis PLS Discriminant Analysis (PLS-DA) is a discriminant analysis performed in order to sharpen the separation between groups of observations, by hopefully rotating PCA (Principal Components Analysis) components such that a maximum separation among classes is obtained, and to understand which variables carry the class separating information. James Malone PLS-DA WEB: http://www.camo.com/rt/Resources/pls-da.html partial least square discriminant analysis eh transformation This type of transformation is typically used in flow cytometry. An eh transformation is a data transformation obtained by applying the function EH described in what follows to a (one dimensional) real number input. EH(x)=exp(x*d/r)+b*(d/r)*x-1, if x>=0, and EH(x)=-exp(-x*d/r)+b*(d/r)*x+1, otherwise. Here exp denotes an exponential transformation and b, d, r are positive real constants with the objective of normalization. Elisabetta Manduchi Joseph Spliden Ryan Brinkman WEB: http://flowcyt.sourceforge.net/gating/latest.pdf eh transformation b transformation This type of transformation is typically used in flow cytometry. A b transformation is a data transformation obtained by applying the function B described in what follows to a (one dimensional) real number input. B(x)= a*exp(b*x)-c*exp(-d*x)+f, where exp denotes an exponential transformation and a, b, c, d, f are real constants with a, b, c, d positive with the objective of normalization. Elisabetta Manduchi Joseph Spliden Ryan Brinkman WEB: http://flowcyt.sourceforge.net/gating/latest.pdf b transformation s transformation This type of transformation is typically used in flow cytometry. An s transformation is a data transformation obtained by applying the function S described in what follows to a (one dimensional) real number input. S(x)=T*exp(w-m)*(exp(x-w)-(p^2)*exp((w-x)/p)+p^2-1) if x>=w, S(x)=-S(w-x) otherwise; where exp denotes an exponential_transformations, 'p^' denotes the exponential transformation with base p; T, w, m, p are real constants with T, m, and p positive and w non-negative, and where w and p are related by w=2p*ln(p)(p+1) with the objective of normalization. Elisabetta Manduchi Joseph Spliden Ryan Brinkman WEB: http://flowcyt.sourceforge.net/gating/latest.pdf s transformation data visualization Generation of a heatmap from a microarray dataset An planned process that creates images, diagrams or animations from the input data. Elisabetta Manduchi James Malone Melanie Courtot Tina Boussard data encoding as image visualization PERSON: Elisabetta Manduchi PERSON: James Malone PERSON: Melanie Courtot PERSON: Tina Boussard Possible future hierarchy might include this: information_encoding >data_encoding >>image_encoding data visualization similarity calculation A similarity calculation is a data transformation that attaches to each pair of objects in the input a number that is meant to reflect how 'close' or 'similar' those objects are. Elisabetta Manduchi PERSON: Elisabetta Manduchi similarity calculation euclidean distance calculation An euclidean distance calculation is a similarity calculation that attaches to each pair of real number vectors of the same dimension n the square root of the sum of the square differences between corresponding components. The smaller this number, the more similar the two vectors are considered. Elisabetta Manduchi PERSON: Elisabetta Manduchi euclidean distance calculation pearson correlation coefficient calculation A pearson correlation coefficient calculation is a similarity calculation which attaches to each pair of random variables X and Y the ratio of their covariance by the product of their standard deviations. Given a series of n measurements of X and Y written as x_i and y_i where i = 1, 2, ..., n, then their Pearson correlation coefficient refers to the "sample correlation coefficient" and is written as the sum over i of the ratios (x_i-xbar)*(y_i-ybar)/((n-1)*s_x*s_y) where xbar and ybar are the sample means of X and Y , s_x and s_y are the sample standard deviations of X and Y. The closer the pearson correlation coefficient is to 1, the more similar the inputs are considered. Elisabetta Manduchi PERSON: Elisabetta Manduchi WEB: http://en.wikipedia.org/wiki/Correlation pearson correlation coefficient calculation loess fitting A loess fitting is a curve fitting obtained by localized regression. The latter refers to fitting a polynomial (straight line, quadratic, cubic, etc) to data values within a window covering a fraction of the total number of observations. As the window slides along the axis, a new polynomial is fit to the observations falling within the window. This continues until all points are fit with a local polynomial. The results are then smoothed together to form a curve. The smoothness of loess fits is controlled by a smoothing parameter (often denoted as alpha, usually between 1/4 and 1) and the degree of the polynomial that is fitted by the method (usually denoted by lambda). Monnie McGee Philippe Rocca-Serra ARTICLE: Mathematical details of loess fits are given in Cleveland, William (1993) Visualizing Data. Hobart Press, Summit, New Jersey, pp. 94-101. loess fitting mode calculation A mode calculation is a descriptive statistics calculation in which the mode is calculated which is the most common value in a data set. It is most often used as a measure of center for discrete data. James Malone Monnie McGee PERSON: James Malone PERSON: Monnie McGee From Monnie's file comments - need to add center_calculation role but it doesn't exist yet - (editor note added by James Jan 2008) mode calculation quantile calculation A quantile calculation is a descriptive statistics calculation in which the kth quantile is the data value for which an approximate k fraction of the data is less than or equal to that value. See http://www.stat.wvu.edu/SRS/Modules/Quantiles/quantiles.html for details. Monnie McGee WEB: http://www.stat.wvu.edu/SRS/Modules/Quantiles/quantiles.html quantile calculation median calculation A median calculation is a descriptive statistics calculation in which the midpoint of the data set (the 0.5 quantile) is calculated. First, the observations are sorted in increasing order. For an odd number of observations, the median is the middle value of the sorted data. For an even number of observations, the median is the average of the two middle values. James Malone Monnie McGee PERSON: James Malone PERSON: Monnie McGee From Monnie's file comments - need to add center_calculation role but it doesn't exist yet - (editor note added by James Jan 2008) median calculation variance calculation A variance calculation is a descriptive statistics calculation in which the variance is defined as the average squared distance of each observation in the data set to the mean of the data set. It is also known as the second central moment. Monnie McGee PERSON: Monnie McGee From Monnie's file comments - need to add spread_calculation and moment_calculation roles but they don't exist yet - (editor note added by James Jan 2008) variance calculation standard deviation calculation A standard deviation calculation is a descriptive statistics calculation defined as the square root of the variance. Also thought of as the average distance of each value to the mean. Monnie McGee PERSON: Monnie McGee From Monnie's file comments - need to add spread calculation role but they doesn't exist yet - (editor note added by James Jan 2008) standard deviation calculation interquartile-range calculation The interquartile range is a descriptive statistics calculation defined as the difference between the 0.75 quantile and the 0.25 quantile for a set of data. Monnie McGee PERSON: Monnie McGee From Monnie's file comments - need to add spread calculation role but they doesn't exist yet - (editor note added by James Jan 2008) interquartile-range calculation skewness calculation A skewness calculation is a descriptive statistics calculation defined as a parameter that describes how much a distribution (or a data set) varies from a bell-shaped curve. See http://www.riskglossary.com/link/skewness.htm for details. It is also known as the third central moment Monnie McGee WEB: http://www.riskglossary.com/link/skewness.htm From Monnie's file comments - need to add moment calculation role but they doesn't exist yet - (editor note added by James Jan 2008) skewness calculation kurtosis calculation A kurtosis calculation is a descriptive statistics calculation defined as a parameter that measures how large or small the tails of a distribution are relative to the mean. For details, see http://davidmlane.com/hyperstat/A53638.html Monnie McGee WEB: http://davidmlane.com/hyperstat/A53638.html From Monnie's file comments - need to add moment calculation role but they doesn't exist yet - (editor note added by James Jan 2008) kurtosis calculation data combination A data transformation in which individual input data elements and values are merged together into a output set of data elements and values. Richard Scheuermann data pooling editor data combination network graph construction A network analysis in which an input data set describing objects and relationships between objects is transformed into an output representation of these objects as nodes and the relationships as edges of a network graph. Richard Scheuermann PERSON: Richard Scheuermann network graph construction weighted network graph construction A network graph construction in which an input data set describing objects and quantitative relationships between objects is transformed into and output representation of these objects as nodes and the quantitative relationships as weighted edges of a network graph. Richard Scheuermann PERSON: Richard Scheuermann weighted network graph construction directed network graph construction A network graph construction in which an input data set describing objects and directional relationships between objects is transformed into and output representation of these objects as nodes and the directional relationships as directed edges of a network graph. Richard Scheuermann PERSON: Richard Scheuermann directed network graph construction node quality calculation A network analysis in which an input data set describing node objects and edge relationships between node objects is used to determine the output quality of one of the node objects in the network. Richard Scheuermann PERSON: Richard Scheuermann node quality calculation node degree calculation A node quality calculation in which an input data set describing object nodes and relationship edges between object nodes is used to enumerate the number of unique relationships of an individual object node. Richard Scheuermann PERSON: Richard Scheuermann node degree calculation quantitative node degree calculation A node quality calculation in which an input data set describing object nodes and quantitative relationship edges between object nodes is used to sum all of the quantitative relationships of an individual object node. Richard Scheuermann PERSON: Richard Scheuermann quantitative node degree calculation node in-degree calculation A node quality calculation in which an input data set describing object nodes and directional relationship edges between object nodes is used to enumerate the number of unique relationships pointing into an individual object node. Richard Scheuermann PERSON: Richard Scheuermann node in-degree calculation node out-degree calculation A node quality calculation in which an input data set describing object nodes and directional relationship edges between object nodes is used to enumerate the number of unique relationships pointing out of an individual object node. Richard Scheuermann PERSON: Richard Scheuermann node out-degree calculation node shortest path identification A node quality calculation in which a path describing the shortest path needed to transverse through connected nodes and edges to arrive at a specific target node in the network. Richard Scheuermann PERSON: Richard Scheuermann node shortest path identification edge quality calculation A network analysis in which an input data set describing node objects and edge relationships between node objects is used to determine the output quality of one of the edge relationships in the network. Richard Scheuermann PERSON: Richard Scheuermann edge quality calculation edge betweenness calculation An edge quality calculation in which the input is a data sets of shortest paths between all pairs of node in the network and the output is the sum of all shortest paths that traverse the specific edge. Richard Scheuermann PERSON: Richard Scheuermann edge betweenness calculation network subgraph quality calculation A network analysis in which an input data set describing node objects and edge relationships between node objects is used to determine the output quality of a subgraph partition of the network. Richard Scheuermann PERSON: Richard Scheuermann network subgraph quality calculation subgraph degree calculation A network subgraph quality calculation in which an input data set describing subgraphs and relationship edges between subgraphs and other network objects is used to enumerate the number of unique relationships of an individual subgraph. Richard Scheuermann PERSON: Richard Scheuermann subgraph degree calculation quantitative subgraph degree calculation A network subgraph quality calculation in which an input data set describing subgraphs and quantitative relationship edges between subgraphs and other network objects is used to sum the quantitative relationships of an individual subgraph. Richard Scheuermann PERSON: Richard Scheuermann quantitative subgraph degree calculation mathematical feature feature is a (parent_class) that describes a characteristic, trait or quality of a data transformation This class is temporary and will be placed outside of data transformation ultimately (if it still remains at all after review) James Malone PERSON: James Malone mathematical feature log base The log base is a feature of a logarithmic function which is defined in http://en.wikipedia.org/wiki/Logarithm. Its value can be any positive real number different from 1. Elisabetta Manduchi logarithm base logarithmic base WEB: http://en.wikipedia.org/wiki/Logarithm log base subgraph in-degree calculation A network subgraph quality calculation in which an input data set describing subgraphs and directional relationship edges between subgraphs and other network objects is used to enumerate the number of unique relationships pointing into an individual subgraph. Richard Scheuermann PERSON: Richard Scheuermann subgraph in-degree calculation subgraph out-degree calculation A network subgraph quality calculation in which an input data set describing subgraphs and relationship edges between subgraphs and other network objects is used to enumerate the number of unique relationships pointing out of an individual subgraph. Richard Scheuermann PERSON: Richard Scheuermann subgraph out-degree calculation intra subgraph connectivity calculation A network subgraph quality calculation in which an input data set describing internal nodes, edges and node degrees is used to determine the average node degree within the subgraph. Richard Scheuermann PERSON: Richard Scheuermann intra subgraph connectivity calculation subgraph modularity calculation A network subgraph quality calculation in which an input data set of subgraph in-degree and out-degree qualities is used to calculate the ratio of indegree to outdegree as a measure of modularity. Richard Scheuermann PERSON: Richard Scheuermann subgraph modularity calculation network graph quality calculation A network analysis in which an input data set describing node objects and edge relationships between node objects is used to determine the output quality of the network as a whole. Richard Scheuermann PERSON: Richard Scheuermann network graph quality calculation unit-variance scaling A unit-variance scaling is a data transformation that divides all measurements of a variable by the standard deviation of that variable. Elisabetta Manduchi Philippe Rocca-Serra autoscaling PMID:16762068 unit-variance scaling MA transformation MA transformations are typically used in microarray data analyses. In this context, the g_i and r_i represent the reporter intensities in the two channels of a 2-channel assay or the reporter intensities in two related one-channel assays. Typically the base used for the logarithm is 2. An MA transformation is a data transformation which takes as input a collection of data points (g_1, r_1), (g_2, r_2), ..., (g_n, r_n) with the r_i and g_i positive real numbers, and whose output is the collection of data points (A_1, M_1), (A_2, M_2), ..., (A_n, M_n) where, for each i, A_i=(log(g_i)+log(r_i))/2 and M_i=log(r_i)-log(g_i). Here log denotes a logarithmic transformation. Elisabetta Manduchi Philippe Rocca-Serra PERSON: Elisabetta Manduchi MA transformation exponential base The exponential base is a feature of an exponential function which is defined in http://en.wikipedia.org/wiki/Exponential_function. Its value can be any positive real number (typically different from 1). Elisabetta Manduchi WEB: http://en.wikipedia.org/wiki/Exponential_function exponential base polynomial degree The polynomial degree is a feature of a polynomial function defined as the highest power of the polynomial's terms, where the terms of a polynomial are the individual summands with the coefficients omitted. Elisabetta Manduchi PERSON: Elisabetta Manduchi polynomial degree number of variables The number of variables is a feature of any function (including polynomial functions) with domain contained in an n-dimensional vector space and is defined as n, the dimension of such space. Elisabetta Manduchi PERSON: Elisabetta Manduchi number of variables agglomerative hierarchical clustering An agglomerative hierarchical clustering is a hierarchical clustering which starts with separate clusters and then successively combines these clusters until there is only one cluster remaining. Elisabetta Manduchi James Malone bottom-up hierarchical clustering PERSON: Elisabetta Manduchi agglomerative hierarchical clustering divisive hierarchical clustering A divisive hierarchical clustering is a hierarchical clustering which starts with a single cluster and then successively splits resulting clusters until only clusters of individual objects remain. Elisabetta Manduchi James Malone top-down hierarchical clustering PERSON: Elisabetta Manduchi divisive hierarchical clustering data partitioning Data partitioning is a data transformation with the objective of partitioning or separating input data into output subsets. James Malone PERSON: Melanie Courtot PERSON: Richard Scheuermann PERSON: Ryan Brinkman data partitioning data vector reduction objective Data vector reduction is a data transformation objective in which k m-dimensional input vectors are reduced to j m-dimensional output vectors, where j is smaller than k. James Malone Richard H. Scheuermann PERSON: Richard H. Scheuermann data vector reduction objective generalized family wise error rate correction method A generalized FWER correction method is a multiple testing procedure that controls the probability of at least k+1 false positives, where k is a user-supplied integer. Monnie McGee gFWER correction Dudoit, Sandrine and van der Laan, Mark J. (2008) Multiple Testing Procedures with Applications to Genomics. New York: Springer , p. 19 generalized family wise error rate correction method quantile number of false positives correction method A quantile number of false positives correction method is a MTP that controls for the pth quantile of the distribution of the number of false positives out of the total number of tests performed' Monnie McGee QNFP Dudoit, Sandrine and van der Laan, Mark J. (2008) Multiple Testing Procedures with Applications to Genomics. New York: Springer , p. 19 quantile number of false positives correction method tail probability for the proportion of false positives correction method A TPPFP correction method is a MTP that controls the probability that the proportion of false positives among all rejected hypotheses is no greater than a constant q, where q is between 0 and 1. Monnie McGee TPPFP correction method Dudoit, Sandrine and van der Laan, Mark J. (2008) Multiple Testing Procedures with Applications to Genomics. New York: Springer , p. 20 tail probability for the proportion of false positives correction method false discovery rate correction method The false discovery rate is a data transformation used in multiple hypothesis testing to correct for multiple comparisons. It controls the expected proportion of incorrectly rejected null hypotheses (type I errors) in a list of rejected hypotheses. It is a less conservative comparison procedure with greater power than familywise error rate (FWER) control, at a cost of increasing the likelihood of obtaining type I errors. . 2011-03-31: [PRS]. creating a defined class by specifying the necessary output of dt allows correct classification of FDR dt Monnie McGee Philippe Rocca-Serra FDR correction method Dudoit, Sandrine and van der Laan, Mark J. (2008) Multiple Testing Procedures with Applications to Genomics. New York: Springer , p. 21 and http://www.wikidoc.org/index.php/False_discovery_rate false discovery rate correction method proportion of expected false positives correction method A proportion of expected false positives correction method is a multiple testing procedure that controls the ratio of the expected value of the numbers of false positives to the expected value of the numbers of rejected hypotheses. Monnie McGee PEFP correction method Dudoit, Sandrine and van der Laan, Mark J. (2008) Multiple Testing Procedures with Applications to Genomics. New York: Springer , p. 21 proportion of expected false positives correction method quantile proportion of false positives correction method A quantile proportion of false positives correction method is a multiple testing procedure that controls the pth quantile of the distribution of the proportion of false positives among the rejected hypothesis (false discovery rate). Monnie McGee QPFP correction method Dudoit, Sandrine and van der Laan, Mark J. (2008) Multiple Testing Procedures with Applications to Genomics. New York: Springer , p. 21 quantile proportion of false positives correction method data transformation objective normalize objective An objective specification to transformation input data into output data Modified definition in 2013 Philly OBI workshop James Malone PERSON: James Malone data transformation objective data normalization objective Quantile transformation which has normalization objective can be used for expression microarray assay normalization and it is referred to as "quantile normalization", according to the procedure described e.g. in PMID 12538238. A normalization objective is a data transformation objective where the aim is to remove systematic sources of variation to put the data on equal footing in order to create a common base for comparisons. Elisabetta Manduchi Helen Parkinson James Malone PERSON: Elisabetta Manduchi PERSON: Helen Parkinson PERSON: James Malone data normalization objective correction objective Type I error correction A correction objective is a data transformation objective where the aim is to correct for error, noise or other impairments to the input of the data transformation or derived from the data transformation itself James Malone PERSON: James Malone PERSON: Melanie Courtot correction objective normalization data transformation A normalization data transformation is a data transformation that has objective normalization. James Malone PERSON: James Malone normalization data transformation averaging data transformation An averaging data transformation is a data transformation that has objective averaging. James Malone PERSON: James Malone averaging data transformation partitioning data transformation A partitioning data transformation is a data transformation that has objective partitioning. James Malone PERSON: James Malone partitioning data transformation partitioning objective A k-means clustering which has partitioning objective is a data transformation in which the input data is partitioned into k output sets. A partitioning objective is a data transformation objective where the aim is to generate a collection of disjoint non-empty subsets whose union equals a non-empty input set. Elisabetta Manduchi James Malone PERSON: Elisabetta Manduchi partitioning objective background correction objective A background correction objective is a data transformation objective where the aim is to remove irrelevant contributions from the measured signal, e.g. those due to instrument noise or sample preparation. Elisabetta Manduchi James Malone PERSON: Elisabetta Manduchi background correction objective curve fitting objective A curve fitting objective is a data transformation objective in which the aim is to find a curve which matches a series of data points and possibly other constraints. Elisabetta Manduchi James Malone PERSON: Elisabetta Manduchi curve fitting objective class discovery data transformation A class discovery data transformation (sometimes called unsupervised classification) is a data transformation that has objective class discovery. James Malone clustering data transformation unsupervised classification data transformation PERSON: James Malone class discovery data transformation Fisher's exact test Fisher's exact test is a data transformation used to determine if there are nonrandom associations between two Fisher's exact test is a statistical significance test used in the analysis of contingency tables where sample sizes are small where the significance of the deviation from a null hypothesis can be calculated exactly, rather than relying on an approximation that becomes exact in the limit as the sample size grows to infinity, as with many statistical tests. James Malone WEB:http://mathworld.wolfram.com/FishersExactTest.html Fisher's exact test center calculation objective A mean calculation which has center calculation objective is a data transformation in which the center of the input data is discovered through the calculation of a mean average. A center calculation objective is a data transformation objective where the aim is to calculate the center of an input data set. James Malone PERSON: James Malone center calculation objective class discovery objective A class discovery objective (sometimes called unsupervised classification) is a data transformation objective where the aim is to organize input data (typically vectors of attributes) into classes, where the number of classes and their specifications are not known a priori. Depending on usage, the class assignment can be definite or probabilistic. James Malone clustering objective discriminant analysis objective unsupervised classification objective PERSON: Elisabetta Manduchi PERSON: James Malone class discovery objective class prediction objective A class prediction objective (sometimes called supervised classification) is a data transformation objective where the aim is to create a predictor from training data through a machine learning technique. The training data consist of pairs of objects (typically vectors of attributes) and class labels for these objects. The resulting predictor can be used to attach class labels to any valid novel input object. Depending on usage, the prediction can be definite or probabilistic. A classification is learned from the training data and can then be tested on test data. James Malone classification objective supervised classification objective PERSON: Elisabetta Manduchi PERSON: James Malone class prediction objective spread calculation objective Spread calculation can be achieved by use of a standard deviation, which measures distance from the mean is a data transformation objective whereby the aim is to the calculate the spread of a dataset, spread is a descriptive statistic which describes the variability of values in a data set Awaiting English definition from Monnie McGee James Malone Person:Helen Parkinson spread calculation objective center calculation data transformation A center calculation data transformation is a data transformation that has objective of center calculation. James Malone PERSON: James Malone center calculation data transformation data vector reduction data transformation A data vector reduction is a data transformation that has objective data vector reduction and that consists of reducing the input vectors k to a smaller number of output vectors j, where j<k. James Malone PERSON: James Malone data vector reduction data transformation scaling objective Scaling gene expression data for cross platform analysis http://www.springerprotocols.com/Abstract/doi/10.1007/978-1-59745-454-4_13 is a data transformation objective where all, or some of a data set is adjusted by some data transformation according to some scale, for example a user defined minimum or maximum Awaiting English definition from Monnie McGee James Malone Person:Helen Parkinson scaling objective descriptive statistical calculation data transformation A descriptive statistical calculation data transformation is a data transformation that has objective descriptive statistical calculation and which concerns any calculation intended to describe a feature of a data set, for example, its center or its variability. James Malone descriptive statistical data analysis PERSON: James Malone descriptive statistical calculation data transformation scaling data transformation A scaling data transformation is a data transformation that has objective scaling. James Malone PERSON: James Malone scaling data transformation error correction objective Application of a multiple testing correction method An error correction objective is a data transformation objective where the aim is to remove (correct for) erroneous contributions arising from the input data, or the transformation itself. James Malone, Helen Parkinson PERSON: James Malone error correction objective sequence analysis data transformation A sequence analysis data transformation is a data transformation that has objective sequence analysis and has the aim of analysing ordered biological data for sequential patterns. James Malone EDITOR sequence analysis data transformation cross validation objective A cross validation objective is a data transformation objective in which the aim is to partition a sample of data into subsets such that the analysis is initially performed on a single subset, while the other subset(s) are retained for subsequent use in confirming and validating the initial analysis. James Malone rotation estimation objective WEB: http://en.wikipedia.org/wiki/Cross_validation cross validation objective merging objective merging of columns from two different data sets A merging objective is a data transformation objective in which the data transformation has the aim of performing a union of two or more sets. James Malone combining objective PERSON: Data Transformation Branch merging objective clustered data visualization A data visualization which has input of a clustered data set and produces an output of a report graph which is capable of rendering data of this type. James Malone clustered data visualization gene list visualization Adata visualization which has input of a gene list and produces an output of a report graph which is capable of rendering data of this type. James Malone gene list visualization classified data visualization A data visualization which has input of a classified data set and produces an output of a report graph which is capable of rendering data of this type. James Malone classified data visualization background corrected data visualization A data visualization which has input of a background corrected data set and produces an output of a report graph which is capable of rendering data of this type. James Malone Monnie McGee background corrected data visualization survival analysis data transformation A data transformation which has the objective of performing survival analysis. James Malone PERSON: James Malone survival analysis data transformation proportional hazards model estimation