Moment-closure approximations for mass-action models
Moment-closure approximations for mass-action models
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DOI：
10.1049/iet-syb:20070031
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发表时间：
2009-01-01
影响因子：
2.3
通讯作者：
Gillespie, C. S.
中科院分区：
文献类型：
--
作者：
Gillespie, C. S.
虽然随机种群模型已被证明是一个强大的工具，在研究过程中产生的机制，在广泛的学科，所有太多的相关数学发展涉及非线性数学，这立即提出了困难和具有挑战性的分析问题，需要解决，如果有用的进展是要取得。一个经常用来估计随机过程的矩的近似是矩闭合。这种近似基本上截断了随机过程的矩方程。给出了一类随机种群模型的边际矩方程和联合矩方程的一般表达式。力矩方程的推广允许这种近似很容易地应用于广泛的模型。可从http://pysbml.googlecode.com/获得软件以实现本文所述的技术。
Although stochastic population models have proved to be a powerful tool in the study of process generating mechanisms across a wide range of disciplines, all too often the associated mathematical development involves nonlinear mathematics, which immediately raises difficult and challenging analytic problems that need to be solved if useful progress is to be made. One approximation that is often employed to estimate the moments of a stochastic process is moment closure. This approximation essentially truncates the moment equations of the stochastic process. A general expression for the marginal- and joint-moment equations for a large class of stochastic population models is presented. The generalisation of the moment equations allows this approximation to be applied easily to a wide range of models. Software is available from http://pysbml.googlecode.com/ to implement the techniques presented here.