生化反应系统中罕见事件的加权次反应方法及参数选择。

Zhouyi Xu, Xiaodong Cai
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引用次数: 3

摘要

Kuwahara和Mura最近开发的加权随机模拟算法(wSSA)和Gillespie等人基于重要性抽样技术提出的改进wSSA为有效估计生化反应系统中罕见事件的概率打开了大门。本文首先将重要性抽样技术应用到随机模拟算法的下一反应方法(NRM)中,建立了加权NRM (wNRM)。然后,我们开发了一种系统的方法来选择重要抽样参数的值,该方法可以应用于wSSA和wNRM。数值结果表明,我们的参数选择方法在仿真效率和精度方面都能显著提高wSSA和wNRM的性能。
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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Weighted next reaction method and parameter selection for efficient simulation of rare events in biochemical reaction systems.

The weighted stochastic simulation algorithm (wSSA) recently developed by Kuwahara and Mura and the refined wSSA proposed by Gillespie et al. based on the importance sampling technique open the door for efficient estimation of the probability of rare events in biochemical reaction systems. In this paper, we first apply the importance sampling technique to the next reaction method (NRM) of the stochastic simulation algorithm and develop a weighted NRM (wNRM). We then develop a systematic method for selecting the values of importance sampling parameters, which can be applied to both the wSSA and the wNRM. Numerical results demonstrate that our parameter selection method can substantially improve the performance of the wSSA and the wNRM in terms of simulation efficiency and accuracy.

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