Performance improvement of genetic algorithm for multiple sequence alignment

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorAmorim, Anderson Rici-
Autor(es): dc.creatorVisotaky, Joao Matheus Verdadeiro-
Autor(es): dc.creatorContessoto, Allan De Godoi-
Autor(es): dc.creatorNeves, Leandro Alves-
Autor(es): dc.creatorSouza, Rogeria Cristiane Gratao De-
Autor(es): dc.creatorValencio, Carlos Roberto-
Autor(es): dc.creatorZafalon, Geraldo Francisco Donega-
Data de aceite: dc.date.accessioned2025-08-21T23:34:21Z-
Data de disponibilização: dc.date.available2025-08-21T23:34:21Z-
Data de envio: dc.date.issued2022-04-30-
Data de envio: dc.date.issued2022-04-30-
Data de envio: dc.date.issued2016-07-02-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/PDCAT.2016.029-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/232629-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/232629-
Descrição: dc.descriptionThe multiple sequence alignment (MSA) is considered one of the most important tasks in Bioinformatics. Nevertheless, with the growth in the amount of genomic data available, it is essential the results with biological significance and an acceptable execution time. Thus, many tools have been proposed with the focus in these two last requirements. Considering the tools, the MSA-GA is of them, which is based on Genetic Algorithms approach, and it is widely used to perform MSA, because its simpler approach and good results. However, the biological significance and execution time are two elements that work in opposite directions, because when more biological significance is desired, more execution time will be wasted, mainly considering the amount of genomic data produced by next generation sequencing recently. Therefore, the implementation of parallel programming can help to smooth this disadvantage. Thus, in the present work we developed a parallel version of the MSA-GA tool using multithread programming, in order to keep the good results produced by the tool and improving its execution time.-
Descrição: dc.descriptionDepartment of Computer Science and Statistics São Paulo State University-
Descrição: dc.descriptionDepartment of Computer Science and Statistics São Paulo State University-
Formato: dc.format69-72-
Idioma: dc.languageen-
Relação: dc.relationParallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectGenetic Algorithm-
Palavras-chave: dc.subjectMultiple Sequence Alignment-
Palavras-chave: dc.subjectMultithreaded Approach-
Título: dc.titlePerformance improvement of genetic algorithm for multiple sequence alignment-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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