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<title lang=en>An integrative modeling framework reveals plasticity of TGF-β signaling.</title>
<creator>Andrieux, Geoffroy</creator>
<creator>Le Borgne, Michel</creator>
<creator>Théret, Nathalie</creator>
<contributor>Dynamics, Logics and Inference for biological Systems and Sequences (Dyliss) ; GESTION DES DONNÉES ET DE LA CONNAISSANCE (IRISA-D7) ; Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA) ; CentraleSupélec - Université de Rennes 1 (UR1) - Télécom Bretagne - Institut National des Sciences Appliquées (INSA) - Institut National de Recherche en Informatique et en Automatique (Inria) - École normale supérieure - Rennes (ENS Rennes) - Centre National de la Recherche Scientifique (CNRS) - Université de Bretagne Sud (UBS) - CentraleSupélec - Université de Rennes 1 (UR1) - Télécom Bretagne - Institut National des Sciences Appliquées (INSA) - Institut National de Recherche en Informatique et en Automatique (Inria) - École normale supérieure - Rennes (ENS Rennes) - Centre National de la Recherche Scientifique (CNRS) - Université de Bretagne Sud (UBS) - Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA) ; CentraleSupélec - Université de Rennes 1 (UR1) - Télécom Bretagne - Institut National des Sciences Appliquées (INSA) - Institut National de Recherche en Informatique et en Automatique (Inria) - École normale supérieure - Rennes (ENS Rennes) - Centre National de la Recherche Scientifique (CNRS) - Université de Bretagne Sud (UBS) - CentraleSupélec - Université de Rennes 1 (UR1) - Télécom Bretagne - Institut National des Sciences Appliquées (INSA) - Institut National de Recherche en Informatique et en Automatique (Inria) - École normale supérieure - Rennes (ENS Rennes) - Centre National de la Recherche Scientifique (CNRS) - Université de Bretagne Sud (UBS) - Inria Rennes – Bretagne Atlantique ; Institut National de Recherche en Informatique et en Automatique (Inria)</contributor>
<contributor>Institut de recherche, santé, environnement et travail [Rennes] (Irset) ; Université d'Angers (UA) - Université des Antilles et de la Guyane (UAG) - Université de Rennes 1 (UR1) - École des Hautes Études en Santé Publique [EHESP] (EHESP) - Institut National de la Santé et de la Recherche Médicale (INSERM) - Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique )</contributor>
<contributor>This work was supported by the Institut National de la Santé et de la Recherche Médicale (INSERM), the Ligue Nationale Contre le Cancer and the National Research Agency (ANR).</contributor>
<description>International audience</description>
<source>ISSN: 1752-0509</source>
<source>EISSN: 1752-0509</source>
<source>BMC Systems Biology</source>
<publisher>BioMed Central</publisher>
<identifier>inserm-00978313</identifier>
<identifier>http://www.hal.inserm.fr/inserm-00978313</identifier>
<identifier>http://www.hal.inserm.fr/inserm-00978313/document</identifier>
<identifier>http://www.hal.inserm.fr/inserm-00978313/file/1752-0509-8-30.pdf</identifier>
<source>http://www.hal.inserm.fr/inserm-00978313</source>
<source>BMC Systems Biology, BioMed Central, 2014, 8 (1), pp.30. 〈10.1186/1752-0509-8-30〉</source>
<identifier>DOI : 10.1186/1752-0509-8-30</identifier>
<relation>info:eu-repo/semantics/altIdentifier/doi/10.1186/1752-0509-8-30</relation>
<identifier>PUBMED : 24618419</identifier>
<relation>info:eu-repo/semantics/altIdentifier/pmid/24618419</relation>
<language>en</language>
<subject lang=en>TGF-β</subject>
<subject lang=en>Discrete dynamic model</subject>
<subject lang=en>Signaling pathways</subject>
<subject lang=en>Guarded transition</subject>
<subject>[SDV.BBM.GTP] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN]</subject>
<subject>[SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]</subject>
<subject>[INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]</subject>
<type>info:eu-repo/semantics/article</type>
<type>Journal articles</type>
<description lang=en>BACKGROUND: The TGF-β transforming growth factor is the most pleiotropic cytokine controlling a broad range of cellular responses that include proliferation, differentiation and apoptosis. The context-dependent multifunctional nature of TGF-β is associated with complex signaling pathways. Differential models describe the dynamics of the TGF-β canonical pathway, but modeling the non-canonical networks constitutes a major challenge. Here, we propose a qualitative approach to explore all TGF-β-dependent signaling pathways. RESULTS: Using a new formalism, CADBIOM, which is based on guarded transitions and includes temporal parameters, we have built the first discrete model of TGF-β signaling networks by automatically integrating the 137 human signaling maps from the Pathway Interaction Database into a single unified dynamic model. Temporal property-checking analyses of 15934 trajectories that regulate 145 TGF-β target genes reveal the association of specific pathways with distinct biological processes. We identify 31 different combinations of TGF-β with other extracellular stimuli involved in non-canonical TGF-β pathways that regulate specific gene networks. Extensive analysis of gene expression data further demonstrates that genes sharing CADBIOM trajectories tend to be co-regulated. CONCLUSIONS: As applied here to TGF-β signaling, CADBIOM allows, for the first time, a full integration of highly complex signaling pathways into dynamic models that permit to explore cell responses to complex microenvironment stimuli.</description>
<date>2014</date>
</dc>
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