• Mon espace de travail
  • Aide IRIS
  • Par Publication Par Personne Par Unité
    • English
    • Français
  • Se connecter
Logo du site

IRIS | Système d’Information de la Recherche Institutionnelle

  • Accueil
  • Personnes
  • Publications
  • Unités
  • Périodiques
UNIL
  • English
  • Français
Se connecter
IRIS
  • Accueil
  • Personnes
  • Publications
  • Unités
  • Périodiques
  • Mon espace de travail
  • Aide IRIS

Parcourir IRIS

  • Par Publication
  • Par Personne
  • Par Unité
  1. Accueil
  2. IRIS
  3. Publication
  4. Synchronous versus asynchronous modeling of gene regulatory networks.
 
  • Détails
Titre

Synchronous versus asynchronous modeling of gene regulatory networks.

Type
article
Institution
UNIL/CHUV/Unisanté + institutions partenaires
Périodique
Bioinformatics  
Auteur(s)
Garg, A.
Auteure/Auteur
Di Cara, A.
Auteure/Auteur
Xenarios, I.
Auteure/Auteur
Mendoza, L.
Auteure/Auteur
De Micheli, G.
Auteure/Auteur
Liens vers les personnes
Xenarios, Ioannis  
Liens vers les unités
Institut Suisse de Bioinformatique  
ISSN
1367-4811
Statut éditorial
Publié
Date de publication
2008
Volume
24
Numéro
17
Première page
1917
Dernière page/numéro d’article
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.
Sujets

Algorithms

Computer Simulation

Gene Expression Regul...

Logistic Models

Models, Genetic

Proteome/genetics

Signal Transduction/g...

Software

PID Serval
serval:BIB_2182CDF3CDC9
DOI
10.1093/bioinformatics/btn336
PMID
18614585
WOS
000258860700013
Permalien
https://iris.unil.ch/handle/iris/64239
Open Access
Oui
Date de création
2012-10-18T07:13:53.076Z
Date de création dans IRIS
2025-05-20T15:50:14Z
Fichier(s)
En cours de chargement...
Vignette d'image
Nom

18614585_BIB_2182CDF3CDC9.pdf

Version du manuscrit

published

Taille

222.89 KB

Format

Adobe PDF

PID Serval

serval:BIB_2182CDF3CDC9.P001

URN

urn:nbn:ch:serval-BIB_2182CDF3CDC92

Somme de contrôle

(MD5):85e1513f2c3de9fc44ba257a3f1aa64b

  • Copyright © 2024 UNIL
  • Informations légales