系统生物学中的随机建模

J. Lei
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引用次数: 30

摘要

许多细胞行为受基因调控网络的调控,其动力学是系统生物学研究的主要课题之一。由于这些反应体系中的分子数很少,因此随机效应很重要。近年来,基因调控网络动力学建模的随机性受到了许多研究者的关注。本文是一篇自成一体的综述,试图提供随机建模的概述。我将介绍具有本征噪声的生化系统建模的主要方程(化学主方程、福克-计划方程、反应速率方程、化学朗之万方程)的推导,并讨论这些公式之间的关系。讨论了动力学参数波动系统的数学表达式。最后,我将介绍精确随机模拟算法和近似显式tau跳跃法进行数值模拟。
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Stochastic Modeling in Systems Biology
Many cellular behaviors are regulated by gene regulation networks, kinetics of which is one of the main subjects in the study of systems biology. Because of the low number molecules in these reacting systems, stochastic effects are significant. In recent years, stochasticity in modeling the kinetics of gene regulation networks have been drawing the attention of many researchers. This paper is a self contained review trying to provide an overview of stochastic modeling. I will introduce the derivation of the main equations in modeling the biochemical systems with intrinsic noise (chemical master equation, Fokker-Plan equation, reaction rate equation, chemical Langevin equation), and will discuss the relations between these formulations. The mathematical formulations for systems with fluctuations in kinetic parameters are also discussed. Finally, I will introduce the exact stochastic simulation algorithm and the approximate explicit tau-leaping method for making numerical simulations.
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