High Performance Multiple Sequence Alignment Algorithms for Comparison of Microbial Genomes

TL;DR

This paper introduces a new parallel indexing scheme for multiple sequence alignment algorithms, improving performance in microbial genome analysis, with empirical validation on Mycoplasma gene sequences.

Contribution

A novel indexing scheme for parallelizing multiple sequence alignment algorithms, addressing existing deficiencies and enhancing computational efficiency.

Findings

Improved alignment performance on microbial genomes

Effective parallelization of dynamic programming algorithms

Validated approach on rpoB gene sequences of Mycoplasma

Abstract

Advances in gene sequencing have enabled in silico analyses of microbial genomes and have led to the revision of concepts of microbial taxonomy and evolution. We explore deficiencies in existing multiple sequence global alignment algorithms and introduce a new indexing scheme to partition the dynamic programming algorithm hypercube scoring tensor over processors based on the dependency between partitions to be scored in parallel. The performance of algorithms is compared in the study of rpoB gene sequences of Mycoplasma species.