生物化学网络内禀噪声随机振荡的振幅分布。

Moritz Lang, Steffen Waldherr, Frank Allgöwer
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引用次数: 10

摘要

内在噪声是生化反应网络中的一种常见现象,可能影响网络状态持续振荡的发生和振幅。为了在时域中评估这种振荡的性质,通常需要进行长期的随机模拟,例如使用Gillespie算法。在本文中,我们提出了一种新的方法来计算振荡的振幅分布,而不需要长期的随机模拟。通过该方法的推导,我们还深入了解了随机振荡的结构特征。该方法适用于一类具有随机振荡的非线性随机微分方程。MAPK级联是几种生化信号传导途径的基本要素。算例表明,即使采用进一步的计算近似,该方法也能准确地预测随机振荡的振幅分布。PACS代码:87.10。锰、87.18。Tt, 87.18。VfMSC代码:92B05, 60G10, 65C30。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Amplitude distribution of stochastic oscillations in biochemical networks due to intrinsic noise.

Intrinsic noise is a common phenomenon in biochemical reaction networks and may affect the occurence and amplitude of sustained oscillations in the states of the network. To evaluate properties of such oscillations in the time domain, it is usually required to conduct long-term stochastic simulations, using for example the Gillespie algorithm. In this paper, we present a new method to compute the amplitude distribution of the oscillations without the need for long-term stochastic simulations. By the derivation of the method, we also gain insight into the structural features underlying the stochastic oscillations. The method is applicable to a wide class of non-linear stochastic differential equations that exhibit stochastic oscillations. The application is exemplified for the MAPK cascade, a fundamental element of several biochemical signalling pathways. This example shows that the proposed method can accurately predict the amplitude distribution for the stochastic oscillations even when using further computational approximations.PACS Codes: 87.10.Mn, 87.18.Tt, 87.18.VfMSC Codes: 92B05, 60G10, 65C30.

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