Separation of time-scales and model reduction for stochastic reaction networks

Details Separation of time-scales and model reduction for stochastic reaction networks Separation of time-scales and model reduction for stochastic reaction networks

2010-11-07

arxiv.org/abs/1011.1672v1

Mathematics

Probability

49 pages, 18 figures

Scientific paper

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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