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Dynamic cellular automata: an alternative to cellular simulation

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FormatText, Article
Subjectcellular simulation; cellular automata; E. coli; genetic circuit
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 pair wise 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/.
Publication date
PublisherIOP
In
  • In Silico Biology 5, no. 2: 139–161.
Peer reviewedYes
NRC publication
This is a non-NRC publication

"Non-NRC publications" are publications authored by NRC employees prior to their employment by NRC.

IdentifierNRC-NINT-148
NPARC number8926197
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Record identifier8a0e66ad-ff4f-4a21-ab3d-b5d3ca95d141
Record created2009-04-23
Record modified2020-04-07
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