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The subtle business of model reduction for stochastic chemical kinetics
Dan T Gillespie1, Yang Cao, Kevin R Sanft
1Dan T. Gillespie Consulting, 30504 Cordoba Place, Castaic, California 91384, USA. gillespiedt@mailaps.org
Abstract:
This paper addresses the problem of simplifying chemical reaction networks by adroitly reducing the number of reaction channels and chemical species. The analysis adopts a discrete-stochastic point of view and focuses on the model reaction set S(1)<=>S(2)-->S(3), whose simplicity allows all the mathematics to be done exactly. The advantages and disadvantages of replacing this reaction set with a single S(3)-producing reaction are analyzed quantitatively using novel criteria for measuring simulation accuracy and simulation efficiency. It is shown that in all cases in which such a model reduction can be accomplished accurately and with a significant gain in simulation efficiency, a procedure called the slow-scale stochastic simulation algorithm provides a robust and theoretically transparent way of implementing the reduction.
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