Multiobjective characteristic-based framework for very-large multiple sequence alignment

Detalhes bibliográficos
Autor(a) principal: Rubio-Largo, Álvaro
Data de Publicação: 2018
Outros Autores: Vanneschi, Leonardo, Castelli, Mauro, Vega-Rodríguez, Miguel A.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/151413
Resumo: Rubio-Largo, Á., Vanneschi, L., Castelli, M., & Vega-Rodríguez, M. A. (2018). Multiobjective characteristic-based framework for very-large multiple sequence alignment. Applied Soft Computing Journal, 69, 719-736. [Advanced online publication on 27 June 2017]DOI: 10.1016/j.asoc.2017.06.022
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spelling Multiobjective characteristic-based framework for very-large multiple sequence alignmentCharacteristic-basedEvolutionary algorithmsMultiobjective optimizationMultiple sequence alignmentSoftwareSDG 3 - Good Health and Well-beingRubio-Largo, Á., Vanneschi, L., Castelli, M., & Vega-Rodríguez, M. A. (2018). Multiobjective characteristic-based framework for very-large multiple sequence alignment. Applied Soft Computing Journal, 69, 719-736. [Advanced online publication on 27 June 2017]DOI: 10.1016/j.asoc.2017.06.022In the literature, we can find several heuristics for solving the multiple sequence alignment problem. The vast majority of them makes use of flags in order to modify certain alignment parameters; however, if no flags are used, the aligner will run with the default parameter configuration, which, often, is not the optimal one. In this work, we propose a framework that, depending on the biological characteristics of the input dataset, runs the aligner with the best parameter configuration found for another dataset that has similar biological characteristics, improving the accuracy and conservation of the obtained alignment. To train the framework, we use three well-known multiobjective evolutionary algorithms: NSGA-II, IBEA, and MOEA/D. Then, we perform a comparative study between several aligners proposed in the literature and the characteristic-based version of Kalign, MAFFT, and MUSCLE, when solving widely-used benchmarks (PREFAB v4.0 and SABmark v1.65) and very-large benchmarks with thousands of unaligned sequences (HomFam).NOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNRubio-Largo, ÁlvaroVanneschi, LeonardoCastelli, MauroVega-Rodríguez, Miguel A.2024-01-27T01:32:01Z20182018-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10362/151413eng1568-4946PURE: 3236565https://doi.org/10.1016/j.asoc.2017.06.022info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:33:52Zoai:run.unl.pt:10362/151413Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:54:34.909210Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Multiobjective characteristic-based framework for very-large multiple sequence alignment
title Multiobjective characteristic-based framework for very-large multiple sequence alignment
spellingShingle Multiobjective characteristic-based framework for very-large multiple sequence alignment
Rubio-Largo, Álvaro
Characteristic-based
Evolutionary algorithms
Multiobjective optimization
Multiple sequence alignment
Software
SDG 3 - Good Health and Well-being
title_short Multiobjective characteristic-based framework for very-large multiple sequence alignment
title_full Multiobjective characteristic-based framework for very-large multiple sequence alignment
title_fullStr Multiobjective characteristic-based framework for very-large multiple sequence alignment
title_full_unstemmed Multiobjective characteristic-based framework for very-large multiple sequence alignment
title_sort Multiobjective characteristic-based framework for very-large multiple sequence alignment
author Rubio-Largo, Álvaro
author_facet Rubio-Largo, Álvaro
Vanneschi, Leonardo
Castelli, Mauro
Vega-Rodríguez, Miguel A.
author_role author
author2 Vanneschi, Leonardo
Castelli, Mauro
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
Vanneschi, Leonardo
Castelli, Mauro
Vega-Rodríguez, Miguel A.
dc.subject.por.fl_str_mv Characteristic-based
Evolutionary algorithms
Multiobjective optimization
Multiple sequence alignment
Software
SDG 3 - Good Health and Well-being
topic Characteristic-based
Evolutionary algorithms
Multiobjective optimization
Multiple sequence alignment
Software
SDG 3 - Good Health and Well-being
description Rubio-Largo, Á., Vanneschi, L., Castelli, M., & Vega-Rodríguez, M. A. (2018). Multiobjective characteristic-based framework for very-large multiple sequence alignment. Applied Soft Computing Journal, 69, 719-736. [Advanced online publication on 27 June 2017]DOI: 10.1016/j.asoc.2017.06.022
publishDate 2018
dc.date.none.fl_str_mv 2018
2018-01-01T00:00:00Z
2024-01-27T01:32:01Z
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 http://hdl.handle.net/10362/151413
url http://hdl.handle.net/10362/151413
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1568-4946
PURE: 3236565
https://doi.org/10.1016/j.asoc.2017.06.022
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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