Mostrar el registro sencillo del ítem

Artículo

dc.creatorZambrano Vega, Cristianes
dc.creatorNebro, Antonio J.es
dc.creatorDurillo, Juan J.es
dc.creatorGarcía Nieto, José Manueles
dc.creatorAldana Montes, José F.es
dc.date.accessioned2021-05-11T08:03:46Z
dc.date.available2021-05-11T08:03:46Z
dc.date.issued2017
dc.identifier.citationZambrano Vega, C., Nebro, A.J., Durillo, J.J., García Nieto, J.M. y Aldana Montes, J.F. (2017). Multiple Sequence Alignment with Multiobjective Metaheuristics. A Comparative Study. International Journal of Intelligent Systems, 32 (8), 843-861.
dc.identifier.issn0884-8173es
dc.identifier.urihttps://hdl.handle.net/11441/108836
dc.description.abstractMultiple sequence alignment (MSA) plays a core role in most bioinformatics studies and provides a framework for the analysis of evolution in biological systems. The MSA problem consists in finding an optimal alignment of three or more sequences of nucleotides or amino acids. Different scores have been defined to assess the quality of MSA solutions, so the problem can be formulated as a multiobjective optimization problem. The number of proposals focused on this approach in the literature is scarce, and most of the works take as base algorithm the NSGA-II metaheuristic. So, there is a lack of a study involving a set of representative multiobjective metaheuristics to deal with this complex problem. Our main goal in this paper is to carry out such study. We propose a biobjective formulation for the MSA and perform an exhaustive comparative study of six multiobjective algorithms. We have considered a number of problems taken from the benchmark BAliBASE (v3.0). Our experiments reveal that the classic NSGA-II algorithm and MOCell, a cellular metaheuristic, provide the best overall performance.es
dc.description.sponsorshipMinisterio de Ciencia e Innovación TIN2014-58304- Res
dc.description.sponsorshipJunta de Andalucía P11-TIC-7529es
dc.description.sponsorshipJunta de Andalucía P12-TIC-1519es
dc.formatapplication/pdfes
dc.format.extent19es
dc.language.isoenges
dc.publisherWileyes
dc.relation.ispartofInternational Journal of Intelligent Systems, 32 (8), 843-861.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleMultiple Sequence Alignment with Multiobjective Metaheuristics. A Comparative Studyes
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/submittedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificiales
dc.relation.projectIDTIN2014-58304- Res
dc.relation.projectIDP11-TIC-7529es
dc.relation.projectIDP12-TIC-1519es
dc.relation.publisherversionhttps://onlinelibrary.wiley.com/doi/full/10.1002/int.21892es
dc.identifier.doi10.1002/int.21892es
dc.journaltitleInternational Journal of Intelligent Systemses
dc.publication.volumen32es
dc.publication.issue8es
dc.publication.initialPage843es
dc.publication.endPage861es
dc.contributor.funderMinisterio de Ciencia e Innovación (MICIN). Españaes
dc.contributor.funderJunta de Andalucíaes

FicherosTamañoFormatoVerDescripción
Multiple sequence alignment.pdf1.078MbIcon   [PDF] Ver/Abrir  

Este registro aparece en las siguientes colecciones

Mostrar el registro sencillo del ítem

Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Excepto si se señala otra cosa, la licencia del ítem se describe como: Attribution-NonCommercial-NoDerivatives 4.0 Internacional