{ "cells": [ { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "\n", "\n", "\n", "***\n", "***" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "# BE 240 Lecture : 2\n", "\n", "## Introduction to SBML\n", "### _Ayush Pandey_\n", "\n", "\n", "## [SBML](http://sbml.org) is a _\"free and open interchange format for computer models of biological processes\"_\n", "\n", "## 1. SBML uses the language of XML\n", "Even the simplest SBML model file can contain hundreds of lines, full of various XML tags. The header looks like this:\n", "```\n", "\n", " \n", "``` \n", "**You don't have to write your own SBML files by hand!**" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "\n", "## 2. Software that support SBML : More than 300! \n", "\n", "* Model building tools: [Tellurium](http://tellurium.analogmachine.org/) (Python), [Sub-SBML](https://github.com/BuildACell/subsbml) (Python), [iBioSim](https://async.ece.utah.edu/tools/ibiosim/) (GUI), [MATLAB SimBiology](https://www.mathworks.com/products/simbiology.html)\n", "* Model simulation tools: [bioscrape](https://github.com/biocircuits/bioscrape/) (Python), [COPASI](http://copasi.org/) (GUI), [LibRoadRunner](http://libroadrunner.org/) (Python), [MATLAB SimBiology](https://www.mathworks.com/products/simbiology.html)\n", "* Analysis tools: [bioscrape inference](https://github.com/biocircuits/bioscrape/) (Python), [COPASI](http://copasi.org/) (GUI), [ABC-SysBio](http://www.theosysbio.bio.ic.ac.uk/resources/abc-sysbio/) (Python)\n", "\n", "Follow [this link](http://sbml.org/SBML_Software_Guide/SBML_Software_Summary) for detailed descriptions of various software tools that support SBML.\n", "\n", "\n", "Models in SBML : A big curated model database : [BioModels](https://www.ebi.ac.uk/biomodels/). An example model from this database at the end of this notebook." ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "## 3. For software developers : SBML API for Python : python-libsbml. \n", "\n", "\n", "* Set/change parameter values: `model.getParameter(6).setValue(1e3)` => Changes the value of the 6th parameter in the list of parameters to 1e3.\n", "* Set initial conditions: `model.getSpecies('id').setInitialAmount(50)` => Changes the initial condition of the species with identifier \"id\" to 50.\n", "\n", "and so on...Not easy to directly use python-libsbml - but you shouldn't need to (unless you are developing your own software). \n", "Refer to the [Documentation](http://sbml.org/Software/libSBML/5.18.0/docs/python-api/) for more information.\n", "\n", "***\n", "---" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "# SBML with bioscrape" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## Important : Update your bioscrape installation \n", "To get the latest changes in bioscrape, run the following from the directory where bioscrape is installed:\n", "```\n", "$ git pull origin master\n", "$ python setup.py install\n", "```\n", "(get the latest code (\"pull\") from the [bioscrape Github repository](https://github.com/ananswam/bioscrape/) master branch, then install bioscrape again).\n", "\n", "We made some bug fixes this week, so it is important that you get the latest version of the package. " ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## Simulating a repressilator circuit (using its SBML model)\n", "From [biomodels](https://www.ebi.ac.uk/biomodels/) SBML model repository, we can get the SBML model that accompanies the original repressilator paper [[1]](https://www.nature.com/articles/35002125). We import the SBML file obtained into bioscrape to simulate it. For more information on how to simulate a bioscrape model, refer to [this](http://www.cds.caltech.edu/%7Emurray/courses/be240/sp2020/W2_bioscrape.ipynb) notebook. " ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "## A quick peek into the SBML model:\n", "Model header: \n", "Species: " ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## The ODE model (from [[1]](https://www.nature.com/articles/35002125.pdf)): \n", "\n", "\n", "In the SBML model: PX: lacI protein, PY: TetR protein, PZ: cI protein." ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "slideshow": { "slide_type": "slide" } }, "outputs": [], "source": [ "# Import bioscrape simulator and import_sbml from sbmlutil to import SBML files into bioscrape.\n", "from bioscrape.sbmlutil import import_sbml\n", "from bioscrape.simulator import py_simulate_model\n", "\n", "# Import the SBML file : Usage : import_sbml('sbml_filename.xml'), returns bioscrape Model object\n", "# (Make sure that the file path is correctly specified wherever the SBML file ending in .xml is present in your directory)\n", "M_represillator = import_sbml('repressilator_sbml.xml')\n", "\n", "#Simulate Deterministically and Stochastically\n", "import numpy as np\n", "timepoints = np.linspace(0,700,10000)\n", "result_det = py_simulate_model(timepoints, Model = M_represillator)\n", "result_stoch = py_simulate_model(timepoints, Model = M_represillator, stochastic = True)\n" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "slideshow": { "slide_type": "skip" } }, "outputs": [ { "data": { "text/plain": [ "
" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" }, { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Import relevant settings and packages to create plots\n", "import matplotlib.pyplot as plt\n", "import matplotlib as mpl\n", "color_list = ['r', 'k', 'b','g','y','m','c']\n", "mpl.rc('axes', prop_cycle=(mpl.cycler('color', color_list) ))\n", "mpl.rc('xtick', labelsize=16) \n", "mpl.rc('ytick', labelsize=16)\n", "plt.figure(figsize = (10, 4))" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "slideshow": { "slide_type": "subslide" } }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "#Plot Results\n", "for i in range(len(M_represillator.get_species_list())):\n", " s = M_represillator.get_species_list()[i]\n", " plt.plot(timepoints, result_det[s], color = color_list[i], label = \"Deterministic \"+s)\n", " plt.plot(timepoints, result_stoch[s], \":\", color = color_list[i], label = \"Stochastic \"+s)\n", "\n", "plt.title('Repressilator Model')\n", "plt.xlabel('Time', FontSize = 16)\n", "plt.ylabel('Amount', FontSize = 16)\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## More examples / assignments:\n", "\n", "1. **Try your own SBML model!** \n", " * Use `M.write_sbml_model(\"filename.xml\")` to write your bioscrape Model object `M` to a SBML file. Then, load up your SBML model as discussed above using `import_sbml`.\n", " * If you are interested, use [Tellurium](http://tellurium.analogmachine.org/) or [COPASI](http://copasi.org/) to create a SBML model, then simulate using bioscrape or compare simulations with other libraries.\n", " * Get a SBML model from one of the repositories online of your favorite paper, then simulate using bioscrape. For example, similar to the repressilator example above, BioModels repository consists SBML models of a \n", " * Toggle Switch \n", " * Influenza Viral Dynamics Spread \n", " * Circadian Oscillator\n", " * MAPK/ERK pathway\n", " * Other interesting examples available [here](https://www.ebi.ac.uk/biomodels/content/model-of-the-month?all=yes).\n", " * Pro Tip : You can directly load an SBML model using the `Model`constructor. Usage : `M = Model(sbml_filename = \"sbml_filename.xml\")`\n", " " ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ " \n", "2. Check out the `Saving and Loading SBML and Bioscrape XML.ipynb` notebook for other examples.\n", "3. We will use [BioCRNpyler](https://github.com/BuildACell/biocrnpyler) next week to generate SBML models of commonly used parts and components in biological circuits. The repository already has quite a few generated SBML models.\n", "4. You can write compartmentalized SBML models for your own project as it might help in the future lectures (different SBML files for each compartment)." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "slideshow": { "slide_type": "skip" } }, "outputs": [], "source": [] } ], "metadata": { "celltoolbar": "Slideshow", "kernelspec": { "display_name": "Python 3.7.4 64-bit", "language": "python", "name": "python37464bita6c5c53d7b16474cae5bc645c5b09138" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.4" } }, "nbformat": 4, "nbformat_minor": 2 }