Título: Abordagem De Enxame De Partículas Cooperativo Paralelo Aplicado Na Otimização Da Predição Da Estrutura De Proteínas Utilizando Modelo AB Em 2D
Autores: Guerra, Fabio Alessandro; Coelho, Leandro dos Santos; Kalegari, Diego Humberto; Pereira, Thiago Enrique Volpe; Ayala, Helon Vicente Hultmann; Coelho, Mariana Cristina
Resumo: Protein structure prediction is a well-known problem in bioinformatics. Identifying protein native conformation makes it possible to predict its function within the organism. Knowing this also helps in the development of new medicines and in comprehending how some illnesses behave. During the past year some techniques have been proposed to solve this problem, but its high cost made it necessary to build models that simplify the protein structures. However, even with the simplicity of these models identifying the protein native conformation remains a highly complex, computationally challenging problem. Particle swarm optimization is a population-based swarm intelligence algorithm that shares many similarities with evolutionary computation techniques. However, this algorithm is driven by the simulation of a social psychological metaphor motivated by collective behaviors of bird and other social organisms instead of the survival of the fittest individual. This paper proposes a Particle Swarm Optimization with a Cooperative and Parallel approach to solve the protein structure prediction problem. The model used to represent the protein structure is the Toy Model (also known as the AB Model) in 2D. This work compares the implementations of three versions of PSO algorithm using a parallel architecture (master-slave).
Palavras-chave: Swarm Intelligence; Cooperative Particle Swarm Optimization; Parallel Computation; Protein Structure Prediction; Toy Model (AB Model)
Código DOI: 10.21528/CBIC2011-06.5
Artigo em pdf: st_06.5.pdf
Arquivo BibTex: st_06.5.bib