Multivariate moment closure techniques for stochastic kinetic models
Multivariate moment closure techniques for stochastic kinetic models
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DOI：
10.1063/1.4929837
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发表时间：
2015-09-07
影响因子：
4.4
通讯作者：
Stumpf, Michael P. H.
中科院分区：
文献类型：
--
作者：
Lakatos, Eszter;Ale, Angelique;Stumpf, Michael P. H.
随机效应主导着许多化学和生化过程。然而，他们的分析，可以是计算昂贵的，已经提出了一系列的近似方案，以减轻计算负担。这些，特别是越来越流行的线性噪声近似和更一般的矩展开方法，表现良好的许多动态制度，特别是线性系统。在更高水平的非线性，它涉及到非线性和随机动力学之间的相互作用，这是很难捕捉正确的这种近似真实的随机过程。矩封闭方法承诺通过捕获时间演化概率分布的高阶项来解决这个问题。在这里，我们开发了一套多变量矩闭包，使我们能够描述非线性系统的随机动力学。多变量封闭捕获的方式，不同的分子物种之间的相关性，诱导的反应动力学，与随机效应相互作用。我们使用多变量高斯，伽玛和对数正态封闭，并说明其使用的上下文中的两个模型，已被证明是具有挑战性的，以前的尝试近似随机动力学：振荡p53和Hes1。此外，我们认为一个更大的系统，ERK介导的促分裂原活化蛋白激酶信号，传统的随机模拟方法产生不可接受的高计算成本。(C)2015 AIP Publishing LLC.
Stochastic effects dominate many chemical and biochemical processes. Their analysis, however, can be computationally prohibitively expensive and a range of approximation schemes have been proposed to lighten the computational burden. These, notably the increasingly popular linear noise approximation and the more general moment expansion methods, perform well for many dynamical regimes, especially linear systems. At higher levels of nonlinearity, it comes to an interplay between the nonlinearities and the stochastic dynamics, which is much harder to capture correctly by such approximations to the true stochastic processes. Moment-closure approaches promise to address this problem by capturing higher-order terms of the temporally evolving probability distribution. Here, we develop a set of multivariate moment-closures that allows us to describe the stochastic dynamics of nonlinear systems. Multivariate closure captures the way that correlations between different molecular species, induced by the reaction dynamics, interact with stochastic effects. We use multivariate Gaussian, gamma, and lognormal closure and illustrate their use in the context of two models that have proved challenging to the previous attempts at approximating stochastic dynamics: oscillations in p53 and Hes1. In addition, we consider a larger system, Erk-mediated mitogen-activated protein kinases signalling, where conventional stochastic simulation approaches incur unacceptably high computational costs. (C) 2015 AIP Publishing LLC.