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Large-scale regulatory and signaling network assembly through linked open data

hal.structure.identifierBiologie du fruit et pathologie [BFP]
dc.contributor.authorLEFEBVRE, Marie
hal.structure.identifierITX - unité de recherche de l'institut du thorax [ITX]
dc.contributor.authorGAIGNARD, Alban
hal.structure.identifierBioComputing
hal.structure.identifierCentrale Lille
dc.contributor.authorFOLSCHETTE, Maxime
hal.structure.identifierCombinatoire et Bioinformatique [LS2N - équipe COMBI]
hal.structure.identifierUniversité de Nantes - UFR des Sciences et des Techniques [UN UFR ST]
hal.structure.identifierLaboratoire des Sciences du Numérique de Nantes [LS2N]
dc.contributor.authorBOURDON, Jérémie
hal.structure.identifierCombinatoire et Bioinformatique [LS2N - équipe COMBI]
hal.structure.identifierÉcole Centrale de Nantes [ECN]
hal.structure.identifierLaboratoire des Sciences du Numérique de Nantes [LS2N]
dc.contributor.authorGUZIOLOWSKI, Carito
dc.date.issued2021
dc.identifier.issn1758-0463
dc.description.abstractEnHuge efforts are currently underway to address the organization of biological knowledge through linked open databases. These databases can be automatically queried to reconstruct regulatory and signaling networks. However, assembling networks implies manual operations due to sourcespecific identification of biological entities and relationships, multiple life-science databases with redundant information, and the difficulty of recovering logical flows in biological pathways. We propose a framework based on Semantic Web technologies to automate the reconstruction of largescale regulatory and signaling networks in the context of tumor cells modeling and drug screening. The proposed tool is pyBRAvo (python Biological netwoRk Assembly), and here we have applied it to a dataset of 910 gene expression measurements issued from liver cancer patients. The tool is publicly available at https://github.com/pyBRAvo/pyBRAvo
dc.description.sponsorshipBIOelectrosynthèse pour le Raffinage des déchets Residuels - ANR-10-BTBR-0002
dc.language.isoen
dc.publisherOxford University Press
dc.rights.urihttp://creativecommons.org/licenses/by/
dc.title.enLarge-scale regulatory and signaling network assembly through linked open data
dc.typeArticle de revue
dc.identifier.doi10.1093/database/baaa113
dc.subject.halInformatique [cs]/Bio-informatique [q-bio.QM]
dc.subject.halSciences du Vivant [q-bio]/Bio-Informatique, Biologie Systémique [q-bio.QM]
dc.subject.halInformatique [cs]/Modélisation et simulation
dc.subject.halInformatique [cs]/Base de données [cs.DB]
dc.subject.halSciences du Vivant [q-bio]
bordeaux.journalDatabase - The journal of Biological Databases and Curation
bordeaux.pagebaaa113
bordeaux.volume2021
bordeaux.peerReviewedoui
hal.identifierhal-03107317
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-03107317v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Database%20-%20The%20journal%20of%20Biological%20Databases%20and%20Curation&rft.date=2021&rft.volume=2021&rft.spage=baaa113&rft.epage=baaa113&rft.eissn=1758-0463&rft.issn=1758-0463&rft.au=LEFEBVRE,%20Marie&GAIGNARD,%20Alban&FOLSCHETTE,%20Maxime&BOURDON,%20J%C3%A9r%C3%A9mie&GUZIOLOWSKI,%20Carito&rft.genre=article


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