A Parallel Multiobjective Metaheuristic for Multiple Sequence Alignment

Detalhes bibliográficos
Autor(a) principal: Rubio-Largo, Álvaro
Data de Publicação: 2018
Outros Autores: Castelli, Mauro, Vanneschi, Leonardo, Vega-Rodríguez, Miguel A.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: https://doi.org/10.1101/103101
Resumo: Rubio-Largo, Á., Castelli, M., Vanneschi, L., & Vega-Rodríguez, M. A. (2018). A Parallel Multiobjective Metaheuristic for Multiple Sequence Alignment. Journal of Computational Biology, 25(9), 1009-1022. DOI: 10.1089/cmb.2018.0031
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spelling A Parallel Multiobjective Metaheuristic for Multiple Sequence AlignmentMemetic computingMetaheuristicMultiobjective optimizationMultiple sequence alignmentModelling and SimulationMolecular BiologyGeneticsComputational MathematicsComputational Theory and MathematicsSDG 3 - Good Health and Well-beingRubio-Largo, Á., Castelli, M., Vanneschi, L., & Vega-Rodríguez, M. A. (2018). A Parallel Multiobjective Metaheuristic for Multiple Sequence Alignment. Journal of Computational Biology, 25(9), 1009-1022. DOI: 10.1089/cmb.2018.0031The alignment among three or more nucleotides/amino acids sequences at the same time is known as multiple sequence alignment (MSA), a nondeterministic polynomial time (NP)-hard optimization problem. The time complexity of finding an optimal alignment raises exponentially when the number of sequences to align increases. In this work, we deal with a multiobjective version of the MSA problem wherein the goal is to simultaneously optimize the accuracy and conservation of the alignment. A parallel version of the hybrid multiobjective memetic metaheuristics for MSA is proposed. To evaluate the parallel performance of our proposal, we have selected a pull of data sets with different number of sequences (up to 1000 sequences) and study its parallel performance against other well-known parallel metaheuristics published in the literature, such as MSAProbs, tree-based consistency objective function for alignment evaluation (T-Coffee), Clustal Ω, and multiple alignment using fast Fourier transform (MAFFT). The comparative study reveals that our parallel aligner obtains better results than MSAProbs, T-Coffee, Clustal Ω, and MAFFT. In addition, the parallel version is around 25 times faster than the sequential version with 32 cores, obtaining an efficiency around 80%.NOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNRubio-Largo, ÁlvaroCastelli, MauroVanneschi, LeonardoVega-Rodríguez, Miguel A.2018-09-20T22:20:25Z2018-09-012018-09-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article14application/pdfapplication/pdfhttps://doi.org/10.1101/103101eng1066-5277PURE: 5868267http://www.scopus.com/inward/record.url?scp=85053186520&partnerID=8YFLogxKhttps://doi.org/10.1101/103101info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T17:34:51Zoai:run.unl.pt:10362/47032Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:05:55.411481Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv A Parallel Multiobjective Metaheuristic for Multiple Sequence Alignment
title A Parallel Multiobjective Metaheuristic for Multiple Sequence Alignment
spellingShingle A Parallel Multiobjective Metaheuristic for Multiple Sequence Alignment
Rubio-Largo, Álvaro
Memetic computing
Metaheuristic
Multiobjective optimization
Multiple sequence alignment
Modelling and Simulation
Molecular Biology
Genetics
Computational Mathematics
Computational Theory and Mathematics
SDG 3 - Good Health and Well-being
title_short A Parallel Multiobjective Metaheuristic for Multiple Sequence Alignment
title_full A Parallel Multiobjective Metaheuristic for Multiple Sequence Alignment
title_fullStr A Parallel Multiobjective Metaheuristic for Multiple Sequence Alignment
title_full_unstemmed A Parallel Multiobjective Metaheuristic for Multiple Sequence Alignment
title_sort A Parallel Multiobjective Metaheuristic for Multiple Sequence Alignment
author Rubio-Largo, Álvaro
author_facet Rubio-Largo, Álvaro
Castelli, Mauro
Vanneschi, Leonardo
Vega-Rodríguez, Miguel A.
author_role author
author2 Castelli, Mauro
Vanneschi, Leonardo
Vega-Rodríguez, Miguel A.
author2_role author
author
author
dc.contributor.none.fl_str_mv NOVA Information Management School (NOVA IMS)
Information Management Research Center (MagIC) - NOVA Information Management School
RUN
dc.contributor.author.fl_str_mv Rubio-Largo, Álvaro
Castelli, Mauro
Vanneschi, Leonardo
Vega-Rodríguez, Miguel A.
dc.subject.por.fl_str_mv Memetic computing
Metaheuristic
Multiobjective optimization
Multiple sequence alignment
Modelling and Simulation
Molecular Biology
Genetics
Computational Mathematics
Computational Theory and Mathematics
SDG 3 - Good Health and Well-being
topic Memetic computing
Metaheuristic
Multiobjective optimization
Multiple sequence alignment
Modelling and Simulation
Molecular Biology
Genetics
Computational Mathematics
Computational Theory and Mathematics
SDG 3 - Good Health and Well-being
description Rubio-Largo, Á., Castelli, M., Vanneschi, L., & Vega-Rodríguez, M. A. (2018). A Parallel Multiobjective Metaheuristic for Multiple Sequence Alignment. Journal of Computational Biology, 25(9), 1009-1022. DOI: 10.1089/cmb.2018.0031
publishDate 2018
dc.date.none.fl_str_mv 2018-09-20T22:20:25Z
2018-09-01
2018-09-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://doi.org/10.1101/103101
url https://doi.org/10.1101/103101
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1066-5277
PURE: 5868267
http://www.scopus.com/inward/record.url?scp=85053186520&partnerID=8YFLogxK
https://doi.org/10.1101/103101
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
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