Separation of Time-scales and Model Reduction for Stochastic Reaction
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چکیده
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.
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تاریخ انتشار 2011