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Analyzing Long-Term Dynamics of Biological Networks with Answer Set Programming

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Emna Ben Abdallah
  • Function : Author
Maxime Folschette
Morgan Magnin

Abstract

The formal study of the dynamics of biological systems raises many problems, e.g., identification of attractors, bifurcations, reachability, that are combinatorial by essence. Making these issues tractable requires to design efficient methods that rely on solid and efficient programming frameworks. During the last decades, Answer Set Programming (ASP) [Baral, 2003] has proven to be a strong logic programming paradigm to deal with the inherent complexity of the biological models, allowing to quickly investigate a wide range of configurations. ASP can efficiently enumerate a large number of answer sets, as well as easily filter the results thanks to constraints based on certain properties. This chapter begins by a motivation of the merits of ASP in biological studies based on a 1 state of the art. The basic concepts about ASP and its use in systems biology are then introduced. After having given an overview of the different issues that can be tackled using ASP, the focus is turned onto one problem that is of critical importance: model-checking with ASP, and more specifically the identification of attractors. The merits of such an approach are then exhibited using case studies. This chapter ends on a summary of the promising perspectives that ASP holds in future works about biological dynamics.
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Dates and versions

hal-03735849 , version 1 (21-07-2022)
hal-03735849 , version 2 (21-11-2022)

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  • HAL Id : hal-03735849 , version 1

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Emna Ben Abdallah, Maxime Folschette, Morgan Magnin. Analyzing Long-Term Dynamics of Biological Networks with Answer Set Programming. 2022. ⟨hal-03735849v1⟩
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