Wishart David S, Yang Robert, Arndt David, Tang Peter, Cruz Joseph
Dept. of Computing Science, University of Alberta, Edmonton, AB, Canada T6G 2E8.
In Silico Biol. 2005;5(2):139-61.
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/.
从Petri网到偏微分方程系统，各种各样的方法已被用于对细胞或生化功能的非常特定的方面进行建模。在这里，我们描述了基于主体或动态细胞自动机（DCA）的方法如何作为一种非常简单但非常通用的方法，用于对许多不同类型的细胞或生化过程进行建模。具体而言，通过使用简单的成对相互作用规则并结合随机物体移动来模拟布朗运动，我们展示了DCA方法如何能够轻松且准确地对扩散、粘性阻力、酶促反应速率过程、新陈代谢（三羧酸循环）以及复杂的遗传回路（阻遏物振荡环）进行建模。我们还展示了DCA方法如何能够准确捕捉许多生物过程的随机性。这项技术的成功与简便表明，许多其他物理性质以及细胞行为中更复杂得多的方面都可以使用DCA方法进行建模。我们开发了一个名为SimCell的易于使用的基于图形的计算机程序，用于执行此处描述的DCA模拟。可从http://wishart.biology.ualberta.ca/SimCell/获取该程序。
