The subtle business of model reduction for stochastic chemical kinetics

Dan T. Gillespie, Yang Cao, Kevin R. Sanft, Linda R. Petzold

Research output: Contribution to journalArticle

22 Scopus citations

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 S1 ↔ S2 → S3, whose simplicity allows all the mathematics to be done exactly. The advantages and disadvantages of replacing this reaction set with a single S3 -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.

Original languageEnglish (US)
Article number064103
JournalJournal of Chemical Physics
Volume130
Issue number6
DOIs
StatePublished - Feb 23 2009

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    Gillespie, D. T., Cao, Y., Sanft, K. R., & Petzold, L. R. (2009). The subtle business of model reduction for stochastic chemical kinetics. Journal of Chemical Physics, 130(6), [064103]. https://doi.org/10.1063/1.3072704