Synchronous versus asynchronous modeling of gene regulatory networks.

Détails

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Etat: Public
Version: Final published version
ID Serval
serval:BIB_2182CDF3CDC9
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Synchronous versus asynchronous modeling of gene regulatory networks.
Périodique
Bioinformatics
Auteur(s)
Garg A., Di Cara A., Xenarios I., Mendoza L., De Micheli G.
ISSN
1367-4811 (Electronic)
ISSN-L
1367-4803
Statut éditorial
Publié
Date de publication
2008
Volume
24
Numéro
17
Pages
1917-1925
Langue
anglais
Résumé
MOTIVATION: In silico modeling of gene regulatory networks has gained some momentum recently due to increased interest in analyzing the dynamics of biological systems. This has been further facilitated by the increasing availability of experimental data on gene-gene, protein-protein and gene-protein interactions. The two dynamical properties that are often experimentally testable are perturbations and stable steady states. Although a lot of work has been done on the identification of steady states, not much work has been reported on in silico modeling of cellular differentiation processes.
RESULTS: In this manuscript, we provide algorithms based on reduced ordered binary decision diagrams (ROBDDs) for Boolean modeling of gene regulatory networks. Algorithms for synchronous and asynchronous transition models have been proposed and their corresponding computational properties have been analyzed. These algorithms allow users to compute cyclic attractors of large networks that are currently not feasible using existing software. Hereby we provide a framework to analyze the effect of multiple gene perturbation protocols, and their effect on cell differentiation processes. These algorithms were validated on the T-helper model showing the correct steady state identification and Th1-Th2 cellular differentiation process.
AVAILABILITY: The software binaries for Windows and Linux platforms can be downloaded from http://si2.epfl.ch/~garg/genysis.html.
Mots-clé
Algorithms, Computer Simulation, Gene Expression Regulation/genetics, Logistic Models, Models, Genetic, Proteome/genetics, Signal Transduction/genetics, Software
Pubmed
Web of science
Open Access
Oui
Création de la notice
18/10/2012 8:13
Dernière modification de la notice
20/08/2019 12:58
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