Accelerating Multiple Sequence Alignments Using Parallel Computing

Multiple sequence alignment (MSA) stands as a critical tool for understanding the evolutionary and functional relationships among biological sequences. Obtaining an exact solution for MSA, termed exact-MSA, is a significant challenge due to the combinatorial nature of the problem. Using the dynamic programming technique to solve MSA is recognized as a highly computationally complex algorithm. To cope with the computational demands of MSA, parallel computing offers the potential for significant speedup in MSA. In this study, we investigated the utilization of parallelization to solve the exact-MSA using three proposed novel approaches. In these approaches, we used multi-threading techniques to improve the performance of the dynamic programming algorithms in solving the exact-MSA. We developed and employed three parallel approaches, named diagonal traversing, blocking, and slicing, to improve MSA performance. The proposed method accelerated the exact-MSA algorithm by around 4x. The suggested approaches could be basic approaches to be combined with many existing techniques. These proposed approaches could serve as foundational elements, offering potential integration with existing techniques for comprehensive MSA enhancement.