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.
"Separation of time-scales and model reduction for stochastic reaction networks." Ann. Appl. Probab. 23 (2) 529 - 583, April 2013. https://doi.org/10.1214/12-AAP841