  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.
