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Hybrid Models and Biological Model Reduction with PyDSTool

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  • Robert Clewley

Abstract

The PyDSTool software environment is designed to develop, simulate, and analyze dynamical systems models, particularly for biological applications. Unlike the engineering application focus and graphical specification environments of most general purpose simulation tools, PyDSTool provides a programmatic environment well suited to exploratory data- and hypothesis-driven biological modeling problems. In this work, we show how the environment facilitates the application of hybrid dynamical modeling to the reverse engineering of complex biophysical dynamics; in this case, of an excitable membrane. The example demonstrates how the software provides novel tools that support the inference and validation of mechanistic hypotheses and the inclusion of data constraints in both quantitative and qualitative ways. The biophysical application is broadly relevant to models in the biosciences. The open source and platform-independent PyDSTool package is freely available under the BSD license from http://sourceforge.net/projects/pydstool/. The hosting service provides links to documentation and online forums for user support.

Suggested Citation

  • Robert Clewley, 2012. "Hybrid Models and Biological Model Reduction with PyDSTool," PLOS Computational Biology, Public Library of Science, vol. 8(8), pages 1-8, August.
    • Handle: RePEc:plo:pcbi00:1002628
    DOI: 10.1371/journal.pcbi.1002628
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    1. Waleed A. Muhanna & Roger Alan Pick, 1994. "Meta-Modeling Concepts and Tools for Model Management: A Systems Approach," Management Science, INFORMS, vol. 40(9), pages 1093-1123, September.
    2. Tian Hong & Jianhua Xing & Liwu Li & John J Tyson, 2011. "A Mathematical Model for the Reciprocal Differentiation of T Helper 17 Cells and Induced Regulatory T Cells," PLOS Computational Biology, Public Library of Science, vol. 7(7), pages 1-13, July.
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    2. Grigorii A. Vasilev & Aleksandra A. Filkova & Anastasia N. Sveshnikova, 2021. "Study of Reversible Platelet Aggregation Model by Nonlinear Dynamics," Mathematics, MDPI, vol. 9(7), pages 1-12, April.

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