Parallel programming has been recently extensively used in the bioinformatics field to develop high-performance computational tools that enable finding efficient solutions to biological problems. This is due to the ability of parallel computing to reduce

Abstract

Parallel programming has been recently extensively used in the bioinformatics field to develop high-performance computational tools that enable finding efficient solutions to biological problems. This is due to the ability of parallel computing to reduce the processing time needed for performing computational complex tasks that manipulate large databases without compromising accuracy. Sequence alignment is one of the major problems in the bioinformatics field, where similarity regions between the biological sequences are identified.
In this paper, a parallel programming implementation of the particle swarm optimization (PSO) technique is proposed to solve the sequence alignment problem using the Message Passing Interface (MPI) library on a Linux cluster. The paper highlights the main steps and design challenges of the proposed parallel PSO algorithm, and presents the experimental results of its execution in terms of accuracy, speedup, and scalability.