{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "*This notebook contains material from [PyRosetta](https://RosettaCommons.github.io/PyRosetta.notebooks);\n", "content is available [on Github](https://github.com/RosettaCommons/PyRosetta.notebooks.git).*" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "< [Frequently Asked Questions/Troubleshooting Tips](http://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/01.03-FAQ.ipynb) | [Contents](toc.ipynb) | [Index](index.ipynb) | [Pose Basics](http://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/02.01-Pose-Basics.ipynb) >

\"Open" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Introduction to PyRosetta" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Rosetta is a suite of algorithms for biomolecular structure prediction and design. Rosetta is\n", "written in C++ and is available from www.rosettacommons.org. PyRosetta is a toolkit in the\n", "programming language Python, which encapsulates the Rosetta functionality by using the\n", "compiled C++ libraries. Python is an easy language to learn and includes modern programming\n", "approaches such as objects. It can be used via scripts and interactively as a command-line\n", "program, similar to MATLABĀ®. The main Rosetta docs can be found here: https://www.rosettacommons.org/docs/latest/Home, and here is another link for getting started: https://www.rosettacommons.org/docs/latest/getting_started/Getting-Started.\n", "\n", "It should be noted, that while some Rosetta/PyRosetta functionality can be achieved on a local computer, a computational cluster is generally recommended to use for more in-depth structure prediction and design tasks. \n", "\n", "\n", "The goals of this first workshop are (1) to have you learn to use PyRosetta both interactively\n", "and by writing programs and (2) to have you learn the PyRosetta functions to access and\n", "manipulate properties of protein structure." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Chapter contributors:**\n", "\n", "- Jason C. Klima (University of Washington; Lyell Immunopharma)\n", "- Kathy Le (Johns Hopkins University); parts of this chapter were adapted from the [PyRosetta book](https://www.amazon.com/PyRosetta-Interactive-Platform-Structure-Prediction-ebook/dp/B01N21DRY8) (J. J. Gray, S. Chaudhury, S. Lyskov, J. Labonte).\n", "- Jared Adolf-Bryfogle (Scripps; Institute for Protein Innovation)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "< [Frequently Asked Questions/Troubleshooting Tips](http://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/01.03-FAQ.ipynb) | [Contents](toc.ipynb) | [Index](index.ipynb) | [Pose Basics](http://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/02.01-Pose-Basics.ipynb) >

\"Open" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.1" }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": {}, "toc_section_display": true, "toc_window_display": false } }, "nbformat": 4, "nbformat_minor": 2 }