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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Frontiers Media S.A.
2016-05-01
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Online Access: | http://journal.frontiersin.org/Journal/10.3389/fgene.2016.00094/full |
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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 |
work_keys_str_mv |
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1725510515401162752 |