Brain Storm Optimization for Multiple Sequence Alignment problem

Brain Storm Optimization (BSO) is one of the most effective swarm intelligence methods for finding optimality in optimization problems by simulating the human brainstorming process. The BSO approach has been effectively used to a wide range of employed in several real-world issues. This study focuses on the use of a hybrid approach in conjunction with the idea of self-organization for multiple sequence alignment (MSA) problems. The term “self-organization” refers to a structure that operates without the need for external intervention. To demonstrate the efficacy of the algorithm, we applied BSO to MSA and evaluated the resulting alignment using the sum-of-pair score (SPS). The efficiency of BSO was evaluated using Benchmark Alignment Database (BAliBASE) reference multiple sequence alignments. The BSO method outperformed some other metaheuristic methods and achieves better alignments than existing MSA techniques.