Stochastic models and numerical algorithms for a class of regulatory gene networks.

Détails

ID Serval
serval:BIB_C2FE6E71EED8
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Stochastic models and numerical algorithms for a class of regulatory gene networks.
Périodique
Bulletin of Mathematical Biology
Auteur(s)
Fournier T., Gabriel J.P., Pasquier J., Mazza C., Galbete J., Mermod N.
ISSN
1522-9602[electronic], 0092-8240[linking]
Statut éditorial
Publié
Date de publication
2009
Volume
71
Numéro
6
Pages
1394-1431
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: ppublish
Résumé
Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.
Mots-clé
Algorithms, Animals, Computer Simulation, Doxycycline/metabolism, Feedback, Physiological/genetics, Gene Expression Regulation/physiology, Gene Regulatory Networks/physiology, Gene Therapy, Green Fluorescent Proteins/genetics, Humans, Kinetics, Linear Models, Markov Chains, Models, Genetic, Protein Multimerization/physiology, Repressor Proteins/metabolism, Stochastic Processes, Trans-Activators/metabolism, Transgenes/genetics
Pubmed
Web of science
Création de la notice
23/03/2009 12:03
Dernière modification de la notice
03/03/2018 21:10
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