Package: sbmltoodepy
SBMLtoODEpyOverviewSBMLtoODEpy is a software package that converts Systems Biology Markup Language (SBML) models into Python classes that can be rapidly incorporated into biomedical systems modeling projects written in Python, such as the multiscale simulation platform CompuCell3D, or used simulated directly as ordinary equations models in Python.AuthorsSteve M. Ruggiero and Ashlee N. Ford Versypt (ashleefv@okstate.edu), School of Chemical Engineering, Oklahoma State UniversityUsageThe simplest use of this package is to use the ParseAndGenerate function to quickly create a python implementation of an SBML model.importsbmltoodepyParseAndCreateModel(inputFilePath,jsonFilePath=None,outputFilePath=None,className="SBMLmodel")The parameters are:inputFilePath: The file path of the SBML model.jsonFilePath: An optional file path that if provided is where the function will create a json file containing all of the model elements. If not provided, a json file will not be created.outputFilePath: An optional file path of where the python model implementation will be created. If not provided, the output path will be assumed to be the same as the input but with a .py extension.className: The name of the class defined by the file created by this function.This creates a new python file containing a class implementing the SBML model.To run the model, instantiate the class and call the RunSimulation method with the desired timestep deltaT and optional specification of tolerances.model=SBMLmodel()model.RunSimulation(deltaT,absoluteTolerance=1e-12,relativeTolerance=1e-6)Installation InstructionsSBMLtoODEpy requires either Python version 3.5, 3.6, or 3.7.
SBMLtoODEpy can be downloaded using pip:pip install sbmltoodepyAlternatively, SBMLtoODEpy can be installed from its source code by running the setup.py file included.python setup.py installTo test the package, use the TestPackage function.importsbmltoodepysbmltoodepy.utilities.TestPackage()The TestPackage function raises a warning about trying to set a constant species and 6 numbers.1.27949533562e-069.42747177955e-101.33080766722e-079.79758065656e-084.05696056523e-072.66117319017e-05These are the average relative errors for species, parameters, and compartments between the model results generated using SBMLtoODEpy and results calculated by COPASI for six different models provided inthe sbmltoodepy/sbml_files subdirectory: Smallbone2013, Borisov2009, Guyton1972, Kerkhoven2013, Waugh2006, and Zi2011, respectively. These examples are discussed in more detail in thetutorial.Supporting Python packagesThe following Python packages were used in this project and are needed to generate and run python models:NumPySciPylibSBMLLinksFor more information on using this package,click here to see the tutorial.For more information on SBML, including specifications and other software that supports SBML,click here for the SBML web siteFor a good source of SBML models,the BioModels repository is a great place to search.For this project's code documentation,click here.For this project's github repository,click here.AcknowledgmentsThe software package described here was made possible in part by funding through the award for project number HR17-057, from the Oklahoma Center for the Advancement of Science and Technology.Community GuidelinesTo contribute a change, users can contact Ashlee Ford Versypt by emailashleefv@okstate.eduor submit a pull request.