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Family relationships: should consensus reign?- consensus clustering for protein families

hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
hal.structure.identifierModels and Algorithms for the Genome [MAGNOME]
dc.contributor.authorNIKOLSKI, Macha
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
hal.structure.identifierModels and Algorithms for the Genome [MAGNOME]
dc.contributor.authorSHERMAN, David James
dc.date.accessioned2024-04-15T09:56:15Z
dc.date.available2024-04-15T09:56:15Z
dc.date.issued2007
dc.identifier.issn1367-4803
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/198817
dc.description.abstractEnMotivation: Reliable identification of protein families is key to phylogenetic analysis, functional annotation and the exploration of protein function diversity in a given phylogenetic branch. As more and more complete genomes are sequenced, there is a need for powerful and reliable algorithms facilitating protein families construction. Results:We have formulated the problem of protein families construction as an instance of consensus clustering, for which we designed a novel algorithm that is computationally efficient in practice and produces high quality results. Our algorithm uses an election method to construct consensus families from competing clustering computations. Our consensus clustering algorithm is tailored to serve the specific needs of comparative genomics projects. First, it provides a robust means to incorporate results from different and complementary clustering methods, thus avoiding the need for an a priori choice that may introduce computational bias in the results. Second, it is suited to large-scale projects due to the practical efficiency. And third, it produces high quality results where families tend to represent groupings by biological function. Availability: This method has been used for Ge´nolevures project to compute protein families of Hemiascomycetous yeasts. The data are available online at http://cbi.labri.fr/Genolevures/fam/ Supplementary information: Supplementary data are available at http://cbi.labri.fr/Genolevures/fam/
dc.language.isoen
dc.publisherOxford University Press (OUP)
dc.subject.encomputational biology
dc.subject.enconsensus clustering
dc.subject.enpattern recognition
dc.title.enFamily relationships: should consensus reign?- consensus clustering for protein families
dc.typeArticle de revue
dc.identifier.doi10.1093/bioinformatics/btl314
dc.subject.halInformatique [cs]/Bio-informatique [q-bio.QM]
dc.subject.halSciences du Vivant [q-bio]/Bio-Informatique, Biologie Systémique [q-bio.QM]
bordeaux.journalBioinformatics
bordeaux.pagee71--e76
bordeaux.volume23
bordeaux.hal.laboratoriesLaboratoire Bordelais de Recherche en Informatique (LaBRI) - UMR 5800*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierinria-00202434
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//inria-00202434v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Bioinformatics&rft.date=2007&rft.volume=23&rft.spage=e71--e76&rft.epage=e71--e76&rft.eissn=1367-4803&rft.issn=1367-4803&rft.au=NIKOLSKI,%20Macha&SHERMAN,%20David%20James&rft.genre=article


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