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In Silico Biology 5, 0015 (2004); ©2004, Bioinformation Systems e.V.  

Dynamic cellular automata: an alternative approach to cellular simulation

David S. Wishart*, Robert Yang, David Arndt, Peter Tang and Joseph Cruz

Depts. of Computing Science and Biological Sciences, University of Alberta, Edmonton, AB, Canada T6G 2E8

* Corresponding author; Email:, phone: +1-780-492 0383

Edited by E. Wingender; received October 04, 2004; revised and accepted November 18, 2004; published December 01, 2004


A wide variety of approaches, ranging from Petri nets to systems of partial differential equations, have been used to model very specific aspects of cellular or biochemical functions. Here we describe how an agent-based or dynamic cellular automata (DCA) approach can be used as a very simple, yet very general method to model many different kinds of cellular or biochemical processes. Specifically, using simple pairwise interaction rules coupled with random object moves to simulate Brownian motion, we show how the DCA approach can be used to easily and accurately model diffusion, viscous drag, enzyme rate processes, metabolism (the Krebís cycle), and complex genetic circuits (the repressilator). We also demonstrate how DCA approaches are able to accurately capture the stochasticity of many biological processes. The success and simplicity of this technique suggests that many other physical properties and significantly more complicated aspects of cellular behavior could be modeled using DCA methods. An easy-to-use, graphically-based computer program, called SimCell, was developed to perform the DCA simulations described here. It is available at

Keywords: cellular simulation, cellular automata, E. coli, genetic circuit