Abstract: 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 Kreb's 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 http://wishart.biology.ualberta.ca/SimCell/.
Keywords: cellular simulation, cellular automata, E. coli, genetic circuit
