BoNesis: a Python-based declarative environment for the verification, reprogramming, and synthesis of Most Permissive Boolean networks - BioInformatique
Communication Dans Un Congrès Année : 2024

BoNesis: a Python-based declarative environment for the verification, reprogramming, and synthesis of Most Permissive Boolean networks

Résumé

BoNesis is a Python library which offers a declarative framework for the synthesis of Boolean networks from advanced dynamical properties, such as reachability, bifurcation, minimal trap spaces, stable states, and mutations. It combines recent theoretical advances on Boolean networks with the Most Permissive update mode and efficient resolution of logic programs expressed in Answer-Set Programming. Its main application domain is the inference of Boolean models from bulk and single-cell gene expression data of cell-fate, differentiation and reprogramming processes. BoNesis is distributed under the GPLv3-compatible free software license CeCILL and is available at https://bnediction.github.io/bonesis.
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Dates et versions

hal-04629083 , version 1 (28-06-2024)

Identifiants

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Stéphanie Chevalier, Déborah Boyenval, Gustavo Magaña-López, Théo Roncalli, Athénaïs Vaginay, et al.. BoNesis: a Python-based declarative environment for the verification, reprogramming, and synthesis of Most Permissive Boolean networks. CMSB 2024: 22nd International Conference on Computational Methods in Systems Biology, 2024, Pisa, Italy. ⟨10.1007/978-3-031-71671-3_6⟩. ⟨hal-04629083⟩
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