Dynamic cellular automata: an alternative approach to cellular simulation. Export

@article{citeulike:461424, 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/.}, address = {Dept. of Computing Science, University of Alberta, Edmonton, AB, Canada T6G 2E8. david.wishart@ualberta.ca}, author = {Wishart, D. S. and Yang, R. and Arndt, D. and Tang, P. and Cruz, J.}, citeulike-article-id = {461424}, citeulike-linkout-0 = {http://view.ncbi.nlm.nih.gov/pubmed/15972011}, citeulike-linkout-1 = {http://www.hubmed.org/display.cgi?uids=15972011}, issn = {1386-6338}, journal = {In Silico Biol}, keywords = {cellsim, simulation}, number = {2}, pages = {139--161}, posted-at = {2008-06-19 19:48:43}, priority = {2}, title = {Dynamic cellular automata: an alternative approach to cellular simulation.}, url = {http://view.ncbi.nlm.nih.gov/pubmed/15972011}, volume = {5}, year = {2005} }

TY - JOUR ID - citeulike:461424 L3 - citeulike-article-id:461424 N2 - 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/. IS - 2 JF - In Silico Biol SN - 1386-6338 AD - Dept. of Computing Science, University of Alberta, Edmonton, AB, Canada T6G 2E8. david.wishart@ualberta.ca EP - 161 TI - Dynamic cellular automata: an alternative approach to cellular simulation. VL - 5 SP - 139 KW - cellsim KW - simulation AU - Wishart, DS AU - Yang, R AU - Arndt, D AU - Tang, P AU - Cruz, J PY - 2005/// UR - http://view.ncbi.nlm.nih.gov/pubmed/15972011 ER -