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• W2036996502 abstract "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." @default.
• W2036996502 created "2016-06-24" @default.
• W2036996502 creator A5036792082 @default.
• W2036996502 date "2010-02-26" @default.
• W2036996502 modified "2023-10-18" @default.
• W2036996502 title "Flux Analysis in Process Models via Causality" @default.
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• W2036996502 doi "https://doi.org/10.4204/eptcs.19.2" @default.
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