Logical modeling and dynamical analysis of cellular networks

The logical (or logic) formalism is increasingly used to model regulatory and signaling networks.Complementing these applications, several groups contributed various methods and tools to support the definition and analysis of logical models.After an introduction to the logical modeling framework a...

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Main Authors: Wassim eAbou-Jaoudé, Pauline eTraynard, Pedro Tiago Monteiro, Julio eSaez Rodriguez, Tomáš eHelikar, Denis eThieffry, Claudine eChaouiya
Format: Article
Language:English
Published: Frontiers Media S.A. 2016-05-01
Series:Frontiers in Genetics
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fgene.2016.00094/full
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spelling doaj-495844bb6c3641148b2d793c15ae18092020-11-24T23:40:14ZengFrontiers Media S.A.Frontiers in Genetics1664-80212016-05-01710.3389/fgene.2016.00094188073Logical modeling and dynamical analysis of cellular networksWassim eAbou-Jaoudé0Pauline eTraynard1Pedro Tiago Monteiro2Julio eSaez Rodriguez3Tomáš eHelikar4Denis eThieffry5Claudine eChaouiya6Ecole Normale SupérieureEcole Normale SupérieureINESC-ID/Instituto Superior Técnico, University of LisbonRWTH Aachen University - Faculty of MedicineUniversity of Nebraska-LincolnEcole Normale SupérieureInstituto Gulbenkian de CiênciaThe logical (or logic) formalism is increasingly used to model regulatory and signaling networks.Complementing these applications, several groups contributed various methods and tools to support the definition and analysis of logical models.After an introduction to the logical modeling framework and to several of its variants, we review here a number of recent methodological advances to ease the analysis of large and intricate networks. In particular, we survey approaches to determine model attractors and their reachability properties, to assess the dynamical impact of variations of external signals, and to consistently reduce large models. To illustrate these developments, we further consider several published logical models for two important biological processes, namely the differentiation of T helper cells and the control of mammalian cell cycle.http://journal.frontiersin.org/Journal/10.3389/fgene.2016.00094/fullattractorssimulationcell cycle controlLogical modelingReachability analysisdiscrete dynamics
collection DOAJ
language English
format Article
sources DOAJ
author Wassim eAbou-Jaoudé
Pauline eTraynard
Pedro Tiago Monteiro
Julio eSaez Rodriguez
Tomáš eHelikar
Denis eThieffry
Claudine eChaouiya
spellingShingle Wassim eAbou-Jaoudé
Pauline eTraynard
Pedro Tiago Monteiro
Julio eSaez Rodriguez
Tomáš eHelikar
Denis eThieffry
Claudine eChaouiya
Logical modeling and dynamical analysis of cellular networks
Frontiers in Genetics
attractors
simulation
cell cycle control
Logical modeling
Reachability analysis
discrete dynamics
author_facet Wassim eAbou-Jaoudé
Pauline eTraynard
Pedro Tiago Monteiro
Julio eSaez Rodriguez
Tomáš eHelikar
Denis eThieffry
Claudine eChaouiya
author_sort Wassim eAbou-Jaoudé
title Logical modeling and dynamical analysis of cellular networks
title_short Logical modeling and dynamical analysis of cellular networks
title_full Logical modeling and dynamical analysis of cellular networks
title_fullStr Logical modeling and dynamical analysis of cellular networks
title_full_unstemmed Logical modeling and dynamical analysis of cellular networks
title_sort logical modeling and dynamical analysis of cellular networks
publisher Frontiers Media S.A.
series Frontiers in Genetics
issn 1664-8021
publishDate 2016-05-01
description The logical (or logic) formalism is increasingly used to model regulatory and signaling networks.Complementing these applications, several groups contributed various methods and tools to support the definition and analysis of logical models.After an introduction to the logical modeling framework and to several of its variants, we review here a number of recent methodological advances to ease the analysis of large and intricate networks. In particular, we survey approaches to determine model attractors and their reachability properties, to assess the dynamical impact of variations of external signals, and to consistently reduce large models. To illustrate these developments, we further consider several published logical models for two important biological processes, namely the differentiation of T helper cells and the control of mammalian cell cycle.
topic attractors
simulation
cell cycle control
Logical modeling
Reachability analysis
discrete dynamics
url http://journal.frontiersin.org/Journal/10.3389/fgene.2016.00094/full
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