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Técnicas de otimização em alinhamentos múltiplos de sequência via Cadeias de Markov

Authors: Nóbrega, Juliano Farias da;

Técnicas de otimização em alinhamentos múltiplos de sequência via Cadeias de Markov

Abstract

Recentemente, a bioinformática tornou-se um recurso imprescindível para a análise e interpretação da grande quantidade de informação biológica gerada pela biologia molecular e pelos sequenciadores de última geração. O processo de comparação dessas biossequências é o ponto de partida para o estudo da evolução e diferenciação dos organismos vivos, além de ser uma das tarefas mais importantes na biologia computacional. Neste trabalho apresenta-se uma abordagem baseada na heurística de Cadeias de Markov para otimização de um algoritmo de alinhamento múltiplo de sequências biológicas, proporcionando resultados com mais qualidade e sem o comprometimento do desempenho da ferramenta MUSCLE, escolhida para dar suporte ao trabalho. As cadeias de Markov foram escolhidas como técnica de otimização devido sua eficiente aplicabilidade em diversos problemas, sobretudo na biologia computacional, pois sua metodologia probabilística torna a aplicação computacionalmente viável, contornando os problemas NP-difícil e apresentando resultados significamente precisos.

Recently, bioinformatics has become an indispensable tool for analyzing and interpreting large amounts of information biological generated by molecular biology and the next-generation sequencers. The comparison process these sequences is the starting point for the study of evolution and differentiation of living organisms as well as being one of the most important tasks in computational biology. This work presents an approach based on Markov chains heuristics for optimization of a multiple alignment algorithm of biological sequences, provides improved quality results and without compromising the performance of MUSCLE tool chosen to support the work.. Markov chains were chosen as optimization technique due to its efficient applicability in various other problems, especially in computational biology, as its probabilistic methodology makes applying computationally feasible, bypassing the NP-hard problems and stating significantly accurate results.

Pós-graduação em Ciência da Computação - IBILCE

Country
Brazil
Keywords

Bionformatics, Bioinformática, Multiple sequence alignment, Alinhamento múltiplo de sequências, Modelos de Makov

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green