Original Research Article
STEPS: Modeling and simulating complex reaction-diffusion systems with Python
Erik De Schutter 1, 2 and Stefan M M . Wils 1, 2*
1 Okinawa Institute of Science and Technology, Japan
2 Theoretical Neurobiology, University of Antwerp, Belgium
2 Theoretical Neurobiology, University of Antwerp, Belgium
In this paper we present STEPS, a simulation platform for modeling and stochastic simulation of coupled reaction-diffusion systems with complex 3-dimensional boundary conditions. Setting up such models is a complicated process that consists of many phases. Older versions of STEPS relied on a static input format that did not cleanly separate these phases, limiting modelers in how they could control the simulation and becoming increasingly complex as new features and new simulation algorithms were added. We solved all of these problems by tightly integrating STEPS with Python, using SWIG to expose our existing simulation code. We describe how this new version deals with model construction, mesh representation and simulation and how the integration of these tasks is assisted by Python.
Keywords: Python, software, simulator, reaction kinetics, 3D diffusion, signaling pathway, scripting
Copyright: © De Schutter and Wils. This is an open-access article subject to an exclusive license agreement between the authors and the Frontiers Research Foundation, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are credited.
*Correspondence: Stefan Wils, Theoretical Neurobiology, Biomedical Sciences Department, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Belgium. stefan@tnb.ua.ac.be
Received: 17 September 2008; paper pending published: 11 November 2008;
Edited by:
Rolf Kötter, Radboud University Nijmegen, The Netherlands
*Correspondence: Stefan Wils, Theoretical Neurobiology, Biomedical Sciences Department, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Belgium. stefan@tnb.ua.ac.be
