On Quantitative Comparison of Chemical Reaction Network Models

Ozan Kahramanoğulları
(University of Trento, Department of Mathematics)

Chemical reaction networks (CRNs) provide a convenient language for modelling a broad variety of biological systems. These models are commonly studied with respect to the time series they generate in deterministic or stochastic simulations. Their dynamic behaviours are then analysed, often by using deterministic methods based on differential equations with a focus on the steady states. Here, we propose a method for comparing CRNs with respect to their behaviour in stochastic simulations. Our method is based on using the flux graphs that are delivered by stochastic simulations as abstract representations of their dynamic behaviour. This allows us to compare the behaviour of any two CRNs for any time interval, and define a notion of equivalence on them that overlaps with graph isomorphism at the lowest level of representation. The similarity between the compared CRNs can be quantified in terms of their distance. The results can then be used to refine the models or to replace a larger model with a smaller one that produces the same behaviour or vice versa.

In Emanuele De Angelis, Grigory Fedyukovich, Nikos Tzevelekos and Mattias Ulbrich: Proceedings of the Sixth Workshop on Horn Clauses for Verification and Synthesis and Third Workshop on Program Equivalence and Relational Reasoning (HCVS/PERR 2019), Prague, Czech Republic, 6-7th April 2019, Electronic Proceedings in Theoretical Computer Science 296, pp. 14–27.
Published: 9th July 2019.

ArXived at: http://dx.doi.org/10.4204/EPTCS.296.5 bibtex PDF
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