Multi-objective genetic algorithms applied to protein sequence alignment. / Aplicação de algoritmos genéricos multi-objetivo para alinhamento de seqüências biológicas.

AUTOR(ES)

Waldo Gonzalo Cancino Ticona

DATA DE PUBLICAÇÃO

2003

RESUMO

The Biological Sequence Alignment is a basic operation in Bioinformatics since it serves as a basis for other processes, i.e. determination of the protein s three-dimensional structure. Due to the large amount of data involved, mathematical and computational methods have been used to solve this problem. Traditionally, the Biological Alignment Sequence Problem is formulated as a single optimization problem. Each solution has a score that reflects the similarity between sequences. Then, the optimization process looks for the best score solution. The Multi-Objective Optimization solves problems with multiple objectives that must be reached. Frequently, there is a solution set that represents a trade-off between the objectives. Evolutionary Algorithms, which are inspired by Darwin s Evolution Theory, have been applied with success in solving this kind of problems. This work formulates the Biological Sequence Alignment as a Multi-Objective Optimization Problem in order to find a set of solutions that represent a trade-off between the extension and the quality of the solutions. Several models of Evolutionary Algorithms for Multi-Objetive Optimization have been applied and were evaluated using several performance metrics found in the literature.

ASSUNTO(S)

otimização multi-objetivo alinhamento de seqüências multi-objective optimization algoritmos evolutivos evolutionary algorithms sequence alignment

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