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Master's Dissertation
DOI
https://doi.org/10.11606/D.55.2006.tde-09052007-100823
Document
Author
Full name
Adriano Kiyoshi Oliveira Ogata
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Carlos, 2006
Supervisor
Committee
Delbem, Alexandre Cláudio Botazzo (President)
Regitano, Luciana Correia de Almeida
Silva, Ivan Nunes da
Title in Portuguese
Multialinhamento de seqüências biológicas utilizando algoritmos genéticos
Keywords in Portuguese
Algoritmos evolutivos
Bioinformática
Multialinhamento
Abstract in Portuguese
Dentro da bioinformática uma das atividades mais realizadas é o alinhamento de seqüências biológicas [1]. Seus resultados são utilizados em várias atividades que desdobram-se em áreas de pesquisa interdisciplinares com geração de diversos subprodutos. Sendo uma das primeiras etapas de tais tarefas, o multialinhamento é então importante para garantir a qualidade dos resultados obtidos em vários estudos do material genético. Para este trabalho espera-se a reprodução dos resultados já publicados na área [2]; [3]; [4]; [5]; [6]). A implementação de um programa de multialinhamento global de seqüências biológicas utilizando uma abordagem iterativa estocástica por algoritmo genético, uma forma relativamente recente [7] de se atacar tal problema. Obtenção de um panorama sobre as soluções alternativas existentes
Title in English
Biological multialignment sequence using genetic algorithms
Keywords in English
Bioinformatic
Evolutiionary algorithms
Multialignment
Abstract in English
Multialignment of biological sequences is one of the most frequently used activities in bioinformatics. The results provided by sequence alignment are used in the solution of other bioinformatics problems. Since a multialignment procedure is one of the first steps of many bioinformatics problems, the condition of an alignment affects the quality of the results obtained for these problems. Multialignment of biological sequences is a complex problem (NP complete) and requires usually heuristics to obtain acceptable performance. Evolutionary algorithms have been used with relevant results. This work aims to find better solutions for the multialignment problem using evolutionary computation. In order to achieve that, this research investigates techniques using evolutionary computation applied to multialignment problem and searches to reproduce their results. Moreover, the development of an approach that performs global multialignment of biological sequences using evolutionary algorithms and an evaluation of the available multialignment techniques are also proposed
 
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revisada_ogata.pdf (719.26 Kbytes)
Publishing Date
2007-05-09
 
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