SEPARATION OF TIME-SCALES AND MODEL REDUCTION FOR STOCHASTIC REACTION NETWORKS
SEPARATION OF TIME-SCALES AND MODEL REDUCTION FOR STOCHASTIC REACTION NETWORKS
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DOI：
10.1214/12-aap841
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发表时间：
2013-04-01
影响因子：
1.8
通讯作者：
Kurtz, Thomas G.
中科院分区：
文献类型：
--
作者：
Kang, Hye-Won;Kurtz, Thomas G.
一个随机模型的化学反应网络是嵌入在一个单参数家庭的模型与物种数和速率常数缩放的权力的参数。一个系统的方法来确定适当的选择，可以应用于大型复杂网络的指数。当缩放意味着子网络具有不同的时间尺度时，子网络可以单独近似，通过分析这些低维近似值，可以深入了解整个网络的行为。
A stochastic model for a chemical reaction network is embedded in a one-parameter family of models with species numbers and rate constants scaled by powers of the parameter. A systematic approach is developed for determining appropriate choices of the exponents that can be applied to large complex networks. When the scaling implies subnetworks have different time-scales, the subnetworks can be approximated separately, providing insight into the behavior of the full network through the analysis of these lower-dimensional approximations.