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A Parallel Niched Pareto Evolutionary Algorithm for Multiple Sequence Alignment

dc.contributor.authorSilva, Fernando José Mateus da
dc.contributor.authorSánchez Pérez, Juan Manuel
dc.contributor.authorGómez Pulido, Juan Antonio
dc.contributor.authorVega Rodríguez, Miguel A.
dc.date.accessioned2026-02-11T13:59:12Z
dc.date.available2026-02-11T13:59:12Z
dc.date.issued2011
dc.description.abstractMultiple sequence alignment is one of the most common tasks in Bioinformatics. However, there are not biologically accurate methods for performing sequence alignment. Genetic Algorithms are adaptive search methods which perform well in large and complex spaces, such as the ones present when aligning a set of sequences. Parallel Genetic Algorithms, not only increase the speed up of the search, but also improve its efficiency, presenting results that are better than those provided by the sum of several sequential Genetic Algorithms. Although these methods are often used to optimize a single objective, they can also be used in multidimensional domains, finding all possible tradeoffs among multiple conflicting objectives. Parallel AlineaGA is an evolutionary algorithm which makes use of a Parallel Genetic Algorithm for performing multiple sequence alignment. We present a multiple objective approach of Parallel AlineaGA that uses a Parallel Niched Pareto Genetic Algorithm. We compare the performance of both versions using eight BAliBASE datasets. We also measure up the quality of the obtained solutions with the ones achieved by T-Coffee and ClustalW2, allowing us to observe that our algorithm reaches for better solutions in the majority of the datasets.eng
dc.description.sponsorshipThis work has been partially supported by the Polytechnic Institute of Leiria (Portugal) and the MSTAR project Reference: TIN2008-06491-C04-04/TIN (MICINN Spain).
dc.identifier.citationda Silva, F.J.M., Pérez, J.M.S., Pulido, J.A.G., Rodríguez, M.A.V. (2011). A Parallel Niched Pareto Evolutionary Algorithm for Multiple Sequence Alignment. In: Rocha, M.P., Rodríguez, J.M.C., Fdez-Riverola, F., Valencia, A. (eds) 5th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB 2011). Advances in Intelligent and Soft Computing, vol 93. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19914-1_22
dc.identifier.doi10.1007/978-3-642-19914-1_22
dc.identifier.isbn9783642199134
dc.identifier.isbn9783642199141
dc.identifier.issn1867-5662
dc.identifier.issn1867-5670
dc.identifier.urihttp://hdl.handle.net/10400.8/15601
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer Berlin Heidelberg
dc.relation.hasversionhttps://link.springer.com/chapter/10.1007/978-3-642-19914-1_22
dc.relation.ispartofAdvances in Intelligent and Soft Computing
dc.relation.ispartof5th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB 2011)
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.titleA Parallel Niched Pareto Evolutionary Algorithm for Multiple Sequence Alignmenteng
dc.typebook part
dspace.entity.typePublication
oaire.citation.endPage165
oaire.citation.startPage157
oaire.citation.title5th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB 2011)
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameSilva
person.givenNameFernando
person.identifier.ciencia-id9D19-84F9-F1CA
person.identifier.orcid0000-0001-9335-1851
person.identifier.scopus-author-id24402946400
relation.isAuthorOfPublication2db213d9-a071-4f43-9544-1295ebb6ffde
relation.isAuthorOfPublication.latestForDiscovery2db213d9-a071-4f43-9544-1295ebb6ffde

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