GillesPy: A Python Package for Stochastic Model Building and Simulation

John H Abel; Brian Drawert; Andreas Hellander; Linda R Petzold

doi:10.1109/LLS.2017.2652448

GillesPy: A Python Package for Stochastic Model Building and Simulation

IEEE Life Sci Lett. 2016 Sep;2(3):35-38. doi: 10.1109/LLS.2017.2652448.

Authors

John H Abel¹, Brian Drawert², Andreas Hellander³, Linda R Petzold²

Affiliations

¹ Department of Systems Biology, Harvard Medical School, Boston, MA 02115 USA and the Department of Chemical Engineering, University of California, Santa Barbara, CA 93106 USA.
² Department of Computer Science, University of California, Santa Barbara, CA 93106 USA.
³ Department of Information Technology, Division of Scientific Computing Uppsala University, Uppsala, Sweden SE-751 85.

Abstract

GillesPy is an open-source Python package for model construction and simulation of stochastic biochemical systems. GillesPy consists of a Python framework for model building and an interface to the StochKit2 suite of efficient simulation algorithms based on the Gillespie stochastic simulation algorithms (SSA). To enable intuitive model construction and seamless integration into the scientific Python stack, we present an easy to understand, action-oriented programming interface. Here, we describe the components of this package and provide a detailed example relevant to the computational biology community.

Keywords: Biological systems; open-source software; stochastic systems; systems biology.

Abstract

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