Formal methods for Hopfield-like networks.

Hedi Ben Amor 1 Fabien Corblin 2 Eric Fanchon 3, * Adrien Elena 4 Laurent Trilling 3 Jacques Demongeot 4, 5 Nicolas Glade 4, *
* Auteur correspondant
1 DyCTiM
TIMC-IMAG - Techniques de l'Ingénierie Médicale et de la Complexité - Informatique, Mathématiques et Applications [Grenoble]
TIMC-IMAG - Techniques de l'Ingénierie Médicale et de la Complexité - Informatique, Mathématiques et Applications [Grenoble]
Abstract : Building a meaningful model of biological regulatory network is usually done by specifying the components (e.g. the genes) and their interactions, by guessing the values of parameters, by comparing the predicted behaviors to the observed ones, and by modifying in a trial-error process both architecture and parameters in order to reach an optimal fitness. We propose here a different approach to construct and analyze biological models avoiding the trial-error part, where structure and dynamics are represented as formal constraints. We apply the method to Hopfield-like networks, a formalism often used in both neural and regulatory networks modeling. The aim is to characterize automatically the set of all models consistent with all the available knowledge (about structure and behavior). The available knowledge is formalized into formal constraints. The latter are compiled into Boolean formula in conjunctive normal form and then submitted to a Boolean satisfiability solver. This approach allows to formulate a wide range of queries, expressed in a high level language, and possibly integrating formalized intuitions. In order to explore its potential, we use it to find cycles for 3-nodes networks and to determine the flower morphogenesis regulatory network of Arabidopsis thaliana. Applications of this technique are numerous and concern the building of models from data as well as the design of biological networks possessing specified behaviors.
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Contributeur : Nicolas Glade <>
Soumis le : vendredi 14 juin 2013 - 12:20:53
Dernière modification le : jeudi 29 septembre 2016 - 01:27:43
Document(s) archivé(s) le : dimanche 15 septembre 2013 - 04:10:54


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Hedi Ben Amor, Fabien Corblin, Eric Fanchon, Adrien Elena, Laurent Trilling, et al.. Formal methods for Hopfield-like networks.. Acta Biotheoretica, Springer Verlag, 2013, 61 (1), pp.21-39. 〈10.1007/s10441-013-9169-5〉. 〈hal-00834160〉



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