Logo do repositório
 
Publicação

A Parallel Multiobjective Metaheuristic for Multiple Sequence Alignment

2018-09-01Artigo científico Acesso aberto
Ver registo simples
dc.contributor.authorRubio-Largo, Álvaro
dc.contributor.authorCastelli, Mauro
dc.contributor.authorVanneschi, Leonardo
dc.contributor.authorVega-Rodríguez, Miguel A.
dc.contributor.institutionNOVA Information Management School (NOVA IMS)
dc.contributor.institutionInformation Management Research Center (MagIC) - NOVA Information Management School
dc.contributor.pblMary Ann Leibert
dc.date.accessioned2018-09-20T22:20:25Z
dc.date.available2018-09-20T22:20:25Z
dc.date.issued2018-09-01
dc.descriptionRubio-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
dc.description.abstractThe 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%.en
dc.description.versionpreprint
dc.description.versionauthorsversion
dc.description.versionpublished
dc.format.extent14
dc.format.extent1848678
dc.format.extent2756931
dc.identifier.doi10.1101/103101
dc.identifier.issn1066-5277
dc.identifier.otherPURE: 5868267
dc.identifier.otherPURE UUID: 7178b540-f568-4956-be64-5d999db988f0
dc.identifier.otherScopus: 85053186520
dc.identifier.otherWOS: 000443955000005
dc.identifier.otherORCID: /0000-0002-8793-1451/work/72856159
dc.identifier.otherORCID: /0000-0003-4732-3328/work/151426705
dc.identifier.urihttp://www.scopus.com/inward/record.url?scp=85053186520&partnerID=8YFLogxK
dc.identifier.urihttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=WOS_CPL&DestLinkType=FullRecord&UT=WOS:000443955000005
dc.identifier.urlhttps://www.scopus.com/pages/publications/85053186520
dc.identifier.urlhttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=WOS_CPL&DestLinkType=FullRecord&UT=WOS:000443955000005
dc.language.isoeng
dc.peerreviewedyes
dc.subjectMemetic computing
dc.subjectMetaheuristic
dc.subjectMultiobjective optimization
dc.subjectMultiple sequence alignment
dc.subjectModelling and Simulation
dc.subjectMolecular Biology
dc.subjectGenetics
dc.subjectComputational Mathematics
dc.subjectComputational Theory and Mathematics
dc.subjectSDG 3 - Good Health and Well-being
dc.titleA Parallel Multiobjective Metaheuristic for Multiple Sequence Alignmenten
dc.typejournal article
degois.publication.firstPage1009
degois.publication.issue9
degois.publication.lastPage1022
degois.publication.titleJournal of Computational Biology
degois.publication.volume25
dspace.entity.typePublication
rcaap.rightsopenAccess

Ficheiros

Principais
A mostrar 1 - 2 de 2
Miniatura
Nome:
Rubio_Largo_LVanneschi_MCastelli_MAVegaRodriguez_Parallel_pre_print.pdf
Tamanho:
1.76 MB
Formato:
Adobe Portable Document Format
Ver/Abrir
Miniatura
Nome:
Parallel_Multiobjective_Metaheuristic_Multiple_Sequence.pdf
Tamanho:
2.63 MB
Formato:
Adobe Portable Document Format
Ver/Abrir

Coleções

NIMS: MagIC - Artigos em revista internacional com arbitragem científica (Peer-Review articles in international journals)