biostudies-otherUnknown12Denis ThieffryPLoS computational biologye1005073https://www.ebi.ac.uk/biostudies/studies/MODEL1607310000biostudies-other27599298Denis ThieffryfalseMbodj2016 - Mesoderm specification during Drosophila development<notes xmlns="http://www.sbml.org/sbml/level3/version1/core"> <body xmlns="http://www.w3.org/1999/xhtml"> <div class="dc:title">Mbodj2016 - Mesoderm specification duringDrosophila development</div><div class="dc:bibliographicCitation"> <p>This model is described in the article:</p> <div class="bibo:title"> <a href="http://identifiers.org/pubmed/27599298" title="Access to this publication">Qualitative Dynamical Modelling Can Formally Explain Mesoderm Specification and Predict Novel Developmental Phenotypes.</a> </div> <div class="bibo:authorList">Mbodj A, Gustafson EH, Ciglar L, Junion G, Gonzalez A, Girardot C, Perrin L, Furlong EE, Thieffry D.</div> <div class="bibo:Journal">PLoS Comput. Biol. 2016 Sep; 12(9): e1005073</div> <p>Abstract:</p> <div class="bibo:abstract"> <p>Given the complexity of developmental networks, it is often difficult to predict the effect of genetic perturbations, even within coding genes. Regulatory factors generally have pleiotropic effects, exhibit partially redundant roles, and regulate highly interconnected pathways with ample cross-talk. Here, we delineate a logical model encompassing 48 components and 82 regulatory interactions involved in mesoderm specification during Drosophila development, thereby providing a formal integration of all available genetic information from the literature. The four main tissues derived from mesoderm correspond to alternative stable states. We demonstrate that the model can predict known mutant phenotypes and use it to systematically predict the effects of over 300 new, often non-intuitive, loss- and gain-of-function mutations, and combinations thereof. We further validated several novel predictions experimentally, thereby demonstrating the robustness of model. Logical modelling can thus contribute to formally explain and predict regulatory outcomes underlying cell fate decisions.</p> </div></div><div class="dc:publisher"> <p>This model is hosted on <a href="http://www.ebi.ac.uk/biomodels/">BioModels Database</a> and identified by: <a href="http://identifiers.org/biomodels.db/MODEL1607310000">MODEL1607310000</a>.</p> <p>To cite BioModels Database, please use: <a href="http://identifiers.org/pubmed/20587024" title="Latest BioModels Database publication">BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models</a>.</p></div><div class="dc:license"> <p>To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to <a href="http://creativecommons.org/publicdomain/zero/1.0/" title="Access to: CC0 1.0 Universal (CC0 1.0), Public Domain Dedication">CC0 Public Domain Dedication</a> for more information.</p></div></body> </notes>2016-07-31T00:00:00Z2025-07-14T17:56:20.976Z2025-03-30T22:37:57.014ZMODEL160731000027599298MAMO_0000030null