Abstract
Generalised Boolean Networks are a well known qualitative model used to analyse the evolution of genetic networks as well as generic biological pathways. Despite the qualitative abstraction due to the few threshold concentration values considered for each biological element in the model, the complexity of the execution of a Generalised Boolean model could be non trivial. In this paper, we propose a tailored process algebra, called Sim-πn, reminiscent of the π-calculus to model GBNs. We further apply the Control Flow Analysis methodology to the resulting computational model for making static (and therefore less computationally expensive) predictions on the dynamical evolution of the investigated networks. The scope is twofold: helping in the setting up of the model, for checking its completeness, and checking the evolution of the model, in terms of the possibility to reach particular threshold values of the biological elements in the model, when varying the initial conditions.
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