Using answer set programming to deal with boolean networks and attractor computation: application to gene regulatory networks of cells - Aix-Marseille Université
Article Dans Une Revue Annals of Mathematics and Artificial Intelligence Année : 2023

Using answer set programming to deal with boolean networks and attractor computation: application to gene regulatory networks of cells

Résumé

Deciphering gene regulatory networks’ functioning is an essential step for better understanding of life, as these networks play a fundamental role in the control of cellular processes. Boolean networks have been widely used to represent gene regulatory networks. They allow to describe the dynamics of complex gene regulatory networks straightforwardly and efficiently. The attractors are essential in the analysis of the dynamics of a Boolean network. They explain that a particular cell can acquire specific phenotypes that may be transmitted over several generations. In this work, we consider a new representation of Boolean networks’ dynamics based on a new semantics used in Answer Set Programming (ASP). We use logic programs and ASP to express and deal with gene regulatory networks seen as Boolean networks, and develop a method to detect all the attractors of such networks. We first show how to represent and deal with general Boolean networks for the synchronous and asynchronous updates modes, where the computation of attractors requires a simulation of these networks’ dynamics. Then, we propose an approach for the particular case of circular networks where no simulation is needed. This last specific case plays an essential role in biological systems. We show several theoretical properties; in particular, simple attractors of the gene networks are represented by the stable models of the corresponding logic programs and cyclic attractors by its extra-stable models. These extra-stable models correspond to the extra-extensions of the new semantics that are not captured by the semantics of stable models. We then evaluate the proposed approach for general Boolean networks on real biological networks and the one dedicated to the case of circular networks on Boolean networks generated randomly. The obtained results for both approaches are encouraging.
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Dates et versions

hal-04179983 , version 1 (13-03-2024)

Identifiants

Citer

Tarek Khaled, Belaid Benhamou, Van-Giang Trinh. Using answer set programming to deal with boolean networks and attractor computation: application to gene regulatory networks of cells. Annals of Mathematics and Artificial Intelligence, 2023, ⟨10.1007/s10472-023-09886-7⟩. ⟨hal-04179983⟩
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