Revisiting the Training of Logic Models of Protein Signaling Networks with a Formal Approach based on Answer Set Programming

Abstract : A fundamental question in systems biology is the construction and training to data of mathematical models. Logic formalisms have become very popular to model signaling networks because their simplicity allows us to model large systems encompassing hundreds of proteins. An approach to train (Boolean) logic models to high-throughput phospho-proteomics data was recently introduced and solved using optimization heuristics based on stochastic methods. Here we demonstrate how this problem can be solved using Answer Set Programming (ASP), a declarative problem solving paradigm, in which a problem is encoded as a logical program such that its answer sets represent solutions to the problem. ASP has significant improvements over heuristic methods in terms of efficiency and scalability, it guarantees global optimality of solutions as well as provides a complete set of solutions. We illustrate the application of ASP with in silico cases based on realistic networks and data.
Type de document :
Communication dans un congrès
D. Gilbert and M. Heiner. CMSB - 10th Computational Methods in Systems Biology 2012, Oct 2012, London, United Kingdom. Springer, 7605, pp.342-361, 2012, CMSB 2012, LNCS. 〈10.1007/978-3-642-33636-2_20〉
Liste complète des métadonnées

Littérature citée [21 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-00737112
Contributeur : Santiago Videla <>
Soumis le : vendredi 21 décembre 2012 - 23:23:45
Dernière modification le : jeudi 14 juin 2018 - 10:54:02
Document(s) archivé(s) le : dimanche 18 décembre 2016 - 10:35:27

Fichiers

paper.pdf
Accord explicite pour ce dépôt

Identifiants

Citation

Santiago Videla, Carito Guziolowski, Federica Eduati, Sven Thiele, Niels Grabe, et al.. Revisiting the Training of Logic Models of Protein Signaling Networks with a Formal Approach based on Answer Set Programming. D. Gilbert and M. Heiner. CMSB - 10th Computational Methods in Systems Biology 2012, Oct 2012, London, United Kingdom. Springer, 7605, pp.342-361, 2012, CMSB 2012, LNCS. 〈10.1007/978-3-642-33636-2_20〉. 〈hal-00737112v2〉

Partager

Métriques

Consultations de la notice

764

Téléchargements de fichiers

302