proceeding Papers A Theory of Model Equivalence


Abstract

We propose a theory for quantitative comparison of models in terms of flux networks obtained from stochastic simulations. The technique is applicable to a range of models from chemical reaction networks to rule-based models. The fluxes of the networks are given by the flow of species instances in stochastic simulations (Kahramanogullar and Lynch (2013)). This makes it possible to define a quantitative notion of equivalence, which includes graph isomorphism of flux networks as a special case. We use the technique for comparing models with respect to their simulations at arbitrary time intervals with varying degrees of accuracy, and for simplifying models when a larger model produces the same behavior as the smaller one. Other more involved queries that we aim to address include queries on emulation of a complex model by a simpler one.



Paper Details

Authors

O. Kahramanogullari,  J. Lynch

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http://research.microsoft.com/apps/pubs/?id=226237

Language

English
.