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An Efficient Probabilistic Population-Based Descent for the Median Genome Problem

hal.structure.identifierModels and Algorithms for the Genome [ MAGNOME]
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
dc.contributor.authorGOËFFON, Adrien
hal.structure.identifierModels and Algorithms for the Genome [ MAGNOME]
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
dc.contributor.authorNIKOLSKI, Macha
hal.structure.identifierModels and Algorithms for the Genome [ MAGNOME]
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
dc.contributor.authorSHERMAN, David James
dc.date.accessioned2024-04-15T09:53:33Z
dc.date.available2024-04-15T09:53:33Z
dc.date.issued2008
dc.date.conference2008-08
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/198614
dc.description.abstractEnWe present a novel population-based local search algorithm for the {\em median genome problem}. The primary result of this article is that this probabilistic approach significantly improves the performance of ancestral genome reconstruction compared to existing methods, making it possible to tackle problems where the contemporary genomes may contain many hundreds of markers. Moreover, our method is not limited to triples of genomes, and thus solves the median genome problem in its generality. We show that in real application cases the computational results are highly robust, suggesting that we can interpret the computed median genomes as candidates carrying the semantics of ancestral architectures.
dc.language.isoen
dc.publisherACM
dc.source.titleProceedings of the 10th annual ACM SIGEVO conference on Genetic and evolutionary computation (GECCO 2008)
dc.subject.enMedian Genome Problem
dc.subject.enprobabilistic neighborhood
dc.subject.enlocal search
dc.title.enAn Efficient Probabilistic Population-Based Descent for the Median Genome Problem
dc.typeCommunication dans un congrès
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]/Intelligence artificielle [cs.AI]
bordeaux.page315-322
bordeaux.hal.laboratoriesLaboratoire Bordelais de Recherche en Informatique (LaBRI) - UMR 5800*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.conference.titleGECCO: Genetic And Evolutionary Computation Conference
bordeaux.countryUS
bordeaux.title.proceedingProceedings of the 10th annual ACM SIGEVO conference on Genetic and evolutionary computation (GECCO 2008)
bordeaux.conference.cityAtlanta
bordeaux.peerReviewedoui
hal.identifierhal-00341672
hal.version1
hal.invitednon
hal.proceedingsoui
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-00341672v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.btitle=Proceedings%20of%20the%2010th%20annual%20ACM%20SIGEVO%20conference%20on%20Genetic%20and%20evolutionary%20computation%20(GECCO%202008)&rft.date=2008&rft.spage=315-322&rft.epage=315-322&rft.au=GO%C3%8BFFON,%20Adrien&NIKOLSKI,%20Macha&SHERMAN,%20David%20James&rft.genre=unknown


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