Flux Analysis in Process Models via Causality

Details Flux Analysis in Process Models via Causality Flux Analysis in Process Models via Causality

2010-02-22

arxiv.org/abs/1002.4061v1

EPTCS 19, 2010, pp. 20-39

Computer Science

Computational Engineering, Finance, and Science

Scientific paper

10.4204/EPTCS.19.2

We present an approach for flux analysis in process algebra models of biological systems. We perceive flux as the flow of resources in stochastic simulations. We resort to an established correspondence between event structures, a broadly recognised model of concurrency, and state transitions of process models, seen as Petri nets. We show that we can this way extract the causal resource dependencies in simulations between individual state transitions as partial orders of events. We propose transformations on the partial orders that provide means for further analysis, and introduce a software tool, which implements these ideas. By means of an example of a published model of the Rho GTP-binding proteins, we argue that this approach can provide the substitute for flux analysis techniques on ordinary differential equation models within the stochastic setting of process algebras.

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