A method for estimating stochastic noise in large genetic regulatory networks
A method for estimating stochastic noise in large genetic regulatory networks
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DOI：
10.1093/bioinformatics/bth479
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发表时间：
2005-01-15
期刊：
影响因子：
5.8
通讯作者：
Bolouri, H
中科院分区：
文献类型：
--
作者：
Orrell, D;Ramsey, S;Bolouri, H
动机：由于参与某些反应的分子数量较少，基因调控网络经常受到随机噪声的影响。网络可以用随机技术模拟，把每个反应都当作随机事件来模拟。然而，随着模型变得越来越大和复杂，解决时间可能会变得过多；特别是当人们希望确定一系列参数或模型结构变化对噪声的影响时。因此，需要快速估计随机噪声的方法。结果：本文提出了一种基于非线性动力学误差增长技术的快速估计任意大小遗传网络噪声特性的算法。该方法也可用于确定简单子系统的解析解。它被证明在许多情况下，包括酵母半乳糖调节途径的原型模型。
Motivation: Genetic regulatory networks are often affected by stochastic noise, due to the low number of molecules taking part in certain reactions. The networks can be simulated using stochastic techniques that model each reaction as a stochastic event. As models become increasingly large and sophisticated, however, the solution time can become excessive; particularly if one wishes to determine the effect on noise of changes to a series of parameters, or the model structure. Methods are therefore required to rapidly estimate stochastic noise.Results: This paper presents an algorithm, based on error growth techniques from non-linear dynamics, to rapidly estimate the noise characteristics of genetic networks of arbitrary size. The method can also be used to determine analytical solutions for simple sub-systems. It is demonstrated on a number of cases, including a prototype model of the galactose regulatory pathway in yeast.