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Compartmental Modeling Software: a fast, discrete stochastic framework for biochemical and epidemiological simulation

Christopher W. Lorton, Joshua L. Proctor, Min K. Roh, Philip A. Welkhoff
doi: https://doi.org/10.1101/609172
Christopher W. Lorton
1Institute for Disease Modeling, Bellevue WA 98005, USA
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  • For correspondence: CMS@idmod.org
Joshua L. Proctor
1Institute for Disease Modeling, Bellevue WA 98005, USA
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  • For correspondence: joshualp@uw.edu CMS@idmod.org
Min K. Roh
1Institute for Disease Modeling, Bellevue WA 98005, USA
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  • For correspondence: joshualp@uw.edu CMS@idmod.org
Philip A. Welkhoff
2Bill and Melinda Gates Foundation, Seattle WA 98109, USA
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Abstract

The compartmental modeling software (CMS) is an open source computational framework that can simulate discrete, stochastic reaction models which are often utilized to describe complex systems from epidemiology and systems biology. In this article, we report the computational requirements, the novel input model language, the available numerical solvers, and the output file format for CMS. In addition, the CMS code repository also includes a library of example model files, unit and regression tests, and documentation. Two examples, one from systems biology and the other from computational epidemiology, are included that highlight the functionality of CMS. We believe the creation of computational frameworks such as CMS will advance our scientific understanding of complex systems as well as encourage collaborative efforts for code development and knowledge sharing.

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  • ↵⋆ Co-first author

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted April 19, 2019.
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Compartmental Modeling Software: a fast, discrete stochastic framework for biochemical and epidemiological simulation
Christopher W. Lorton, Joshua L. Proctor, Min K. Roh, Philip A. Welkhoff
bioRxiv 609172; doi: https://doi.org/10.1101/609172
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Compartmental Modeling Software: a fast, discrete stochastic framework for biochemical and epidemiological simulation
Christopher W. Lorton, Joshua L. Proctor, Min K. Roh, Philip A. Welkhoff
bioRxiv 609172; doi: https://doi.org/10.1101/609172

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