This is the core set of predicates used to model phenotypes and the parent class for phenotypes.
currently spo ephys since it describes the changes in phys in response to repeated stimulation
Expresses a relationship between a neuron type and some anatomical criteria, such as being located in a particular system. Note that this NOT a subPropertOf hasLocationPhenotype.
This is used to differentiate things like parasympathetic preganglionic from raw hasPhenotype. This can be used in cases where the meaning is clear to the domain experts, but has not been fully formalized.
a weak property that only asserts that distally there is expected to be at least one case of a hasAxonSensorySubcellularElementIn region in the partial order
not clear whether this should be subPropertyOf hasMorphologicalPhenotype
Expresses a relationship between a neuron type and some phenotype of its axon.
Use to provide clarity about where a generic phenotype is attached in the event that the object is not qualified. The alternative is to precompose the subcompartments e.g. SmallSomaPhenotype and SmallAxonPhenotype.
Expresses a relationship between a neuron and an axon sensory subcellular structure. Should be used to describe e.g. nerve ending types.
Expresses a relationship between a neuron type and a biological sex. This should be used when a neuron type has been observed in a specific sex.
Expresses a relationship between a neuron type and an opaque symbol that is used by experts to distinguish subtypes.
Use this when numbers or letters have been assigned to disambiguate naming.
Expresses a relationship between a neuron type and a type computed from only molecular data.
Expresses a relationship between a neuron type and a type computed from only DNA data (e.g. epigenetics data).
Expresses a relationship between a neuron type and a type computed from only Protein expression data.
Expresses a relationship between a neuron type and a type computed from only RNA expression data.
Expresses a relationship between a neuron type and a type computed from some combination of primary data types.
traditionally harder to get granular types here?
specificity of connections often require pharm
Expresses a relationship between a neuron type and a neuron type or a neuron type and a subcompartment of a neuron type some members are connected with eachother.
Absent a specific subcompartment we can only infer hasProjectionPhenotype at the granularity of soma + dendrite location. NOTE: This relationship does not imply direction. If you need direction please choose a subproperty.
Expresses a relationship between a neuron and a dendrite phenotype. This should be used when a neuron type is described by the morphology of its dendrites.
Expresses a relationship between a neuron type and some phenotype of its dendrite.
Expresses a relationship between a neuron type and a developmental stage. This should be used when a neuron type has been observed during a developmental stage.
Expresses a relationship between a neuron type and a developmental cell population. This should be used when a neuron develops from an identified developmental anatomical entity.
Expresses a relationship between a neuron type and a developmental cell population. This should be used when a neuron develops from an identified developmental cell type.
Expresses a relationship between a neuron type and an electrophysiological phenotype concept. This should be used when a neuron type is described using a high level electrophysiological concept class.
Expresses a relationship between a neuron and an experimental condition. This should be used when a neuron type is described by some experimental condition or functional designation.
This needs a better name. It is clear what it means when you see examples of the usage.
Expresses a relationship between a neuron type and a gene type including any gene products.
This may also include the products of molecular synthesis pathways that are indirectly supported by genes, however it seems likely that that relationship should not be though of as an expression phenotype.
can be inferred from symmetric connection + projects to
Expresses a relationship between a neuron and the immediate effect that it has on post synaptic cells. This is usually either excitatory or inhibitory.
this is currently a subproperty of hasPhenotype because we need to work out the relationship between circuit role and projection phenotype
Expresses a relationship between a neuron and some external property such as high level sensory function.
This should probably be equivalent to hasExperimentalPhenotype, however experimental phenotype implies that the value was actually determined experimentally for a given individual which functional does not necessarily imply.
Expresses a relationship between a neuron type and a species. This should be used when a neuron type has been observed in a specific species.
should rarely be used, even if dealing with evidence based models because it is an extremely weak assertion, possibly rename to hasBeenObservedInAtLeastOneIndividualInSpecies or something like that
Expresses a relationship between a neuron type and a taxon. When dealing with both EBMs and CUTs this is the predicate that should be used.
this is the weakest assertion we have available at a taxon level, hasInstanceInSpecies is even weaker since it does not propagage
Expresses a relationship between a neuron type and a laminar brain region.
May need hasSomaLayerLocation or something, do we really even need this?? if axioms are missing in parcellation schemes and uberon then it should be easy enough to add them, or at least we won't get disjointness issues because layers of cortex are orthogonal to parts of cortex (eg) and thus we shouldnt get reasoning errors
Expresses a relationship between a neuron type and a brain region or brain parcel. This is a superProperty and should not be used directly.
This property should not be used directly.
Expresses a relationship between a neuron type and a molecule type, a gene type, or a gene product type.
This can be used for detection of the molecule or gene by any means.
Expresses a relationship between a neuron type and a morphological phenotype concept. This should be used when a neuron type is described using a high level morphological concept class.
Expresses a relationship between a neuron type and a neurotransmitter that is released from vesicles contained within neurons of that neuron type.
includes small molecule and peptide, not entirely sure if we need this one, we do because expression and release are not 1:1
This should be used for detection of RNAs that code for proteins which may or may not have been detected directly.
Expresses a restriction that modifies all phenotypes associated with a neuron type or a logical phenotype, only meaningful when used inside of owl:intersectionOf
DO NOT USE, AMBIGUOUS! projectsTo does not work because of dendrodentritic synapses, for the same reason this cannot be a subProperty of hasAxonLocatedIn
DO NOT USE, AMBIGUOUS! Are there cases where there are boutons that form on dendrites?
Expresses a relationship between a neuron type and whether the target region it projects to is on the same, opposite, or both sides of the brain.
ispilateral, contralateral, and bilateral are kind of like cortico thalamic but they are lifted to an invariant form that doesn’t care about the exact starting side, unilateral is the union of ipsi and contra but I’m fairly certain that unilateral should never be reported because it is ambiguous, this is primarily a convenience relation for neurons that have a single projection laterality, however there are plenty of examples where there are neurons that project to two different regions one of which is ipsi and the other of which is contra, those cases require the composition to happen on the object of the restriction, so you wind up with has projection phenotype some ipsilateral region, otherwise all our definitions are consistent with bilateral and unilateral projections, which is something we will probably have to fix, right now we are using the PATO laterality terms but the modelling isn’t really what we want because we need to have ipsilateral disjoint from contralateral and disjoint from bilateral
Expresses a relationship between a neuron type and a brain region that said neuron type sends axons to.
this might be clearer than hasCircuitRole but might confuse with projectsTo or the like, excitatory/inhibitory shouldn't be handled here? The way that projection vs intrinsic is modelled relates whether axons leave the brain region that contains the soma or not, this is not fully modelled at the moment
Expresses a relationship between a neuron and a nervous system region where that neuron has a part which is involved in the direct detection of sensory stimuli.
This is the equivalent of axon terminals for sensory dendrites in the peripheral nervous system. Not 100% sure on the modeling, but some mechanosensory neurons this would be the anatomcal region(s) where the Pacinian corpuscle are located.
Expresses a relationship between a neuron and a small molecule that is the product of some molecular pathway that may or may not be expressed in the neuron in question.
This would probably be used to indicate the detection of the machinery for the synthesis pathway. If just the molecule is detected then hasMolecularPhenotype should be used since expression cannot be inferred (for neurotransmitters).
Expresses a relationship between a neuron type and some phenotype of its soma.
Expresses a relationship between a neuron type and a taxon. This should be used when a neuron type is thought to have been present in the last common ancestor of the taxon.
note that this is a subPropertyOf hasInstanceInTaxon NOT the other way around, aka isAncestralInTaxon, even stronger claim than instance and propagates downward implying that instances were present in all members except those specifically marked (which owl can't really support)
currently spo functional, I think this is general to any external metric where the response of a neuron behaves non-linearly across a set threshold
Expresses a relationship between a neuron type and a circuit type that the neuron type is a member of. Implies that individual neurons of that type each have at least one forward or reverse connection with some other member of that circuit type.
Expresses a relationship between a phenotype and a phenotype. This should be used when two phenotypes commonly cooccure.
this is not the right way to pull this off, need something akin to disjointness
Expresses a relationship between a phenotype and a brain region. This should be used when a neuron phenotype is observed in specific brain regions.
of course this can never be universal, so is mostly useful for the python representation
Expresses a relationship between a neuron type and a brain region where said neuron type has a reverse connection phenotype with some neuron type that has its soma located in said brain region.
this is essentially hasReverseProjectionPhenotype, however, unlike for connection phenotypes where forward and reverse are not ambiguous, a reverse projection is a confusing concept and thus not used
A Phenotype is a binary property of a biological entity. Phenotypes are derived from measurements made on the subject of interest. While Phenotype is not currently placed within the BFO hierarchy, if we were to place it, it would fall under BFO:0000016 -> disposition, since these phenotypes are contingent on the experimental conditions under which measurements were made and are NOT qualities. For consideration: in theory this would mean that disjointness does not make sense, even for things that would seem to be obviously disjoint such as Accommodating and Non-Accommodating. However, this information can still be captured on a subject by subject basis by asserting that for this particular entity, coocurrance of phenotypes is not possible. This still leaves the question of whether the class of biological entities that correspond to the bag of phenotypes is implicitly bounded/limited only to the extrinsic and unspecified experimental conditions, some of which are not and cannot be included in a bag of phenotypes. The way to deal with this when we want to include 2 'same time' disjoint phenotypes, is to use a logical phenotype to wrap them with an auxiliary variable that we think accounts for the difference.