Identification of Bifurcations in Biological Regulatory Networks using Answer-Set Programming

Abstract : Aiming at assessing differentiation processes in complex dy-namical systems, this paper focuses on the identification of states and transitions that are crucial for preserving or preempting the reachabil-ity of a given behaviour. In the context of non-deterministic automata networks, we propose a static identification of so-called bifurcations, i.e., transitions after which a given goal is no longer reachable. Such transitions are naturally good candidates for controlling the occurrence of the goal, notably by modulating their propensity. Our method combines Answer-Set Programming with static analysis of reachability properties to provide an under-approximation of all the existing bifurcations. We illustrate our discrete bifurcation analysis on several models of biological systems, for which we identify transitions which impact the reachability of given long-term behaviour. In particular, we apply our implementation on a regulatory network among hundreds of biological species, supporting the scalability of our approach.
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Contributor : Louis Fippo Fitime <>
Submitted on : Wednesday, September 7, 2016 - 11:03:14 AM
Last modification on : Wednesday, December 19, 2018 - 3:02:05 PM
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Louis Fippo Fitime, Olivier Roux, Carito Guziolowski, Loïc Paulevé. Identification of Bifurcations in Biological Regulatory Networks using Answer-Set Programming. Constraint-Based Methods for Bioinformatics Workshop, Sep 2016, Toulouse, France. ⟨hal-01361350⟩



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