Fast vectorized distance matrix computation for multiple sequence alignment on multi-cores

Although high quality multiple sequence alignment is an essential task in bioinformatics, it becomes a big dilemma nowadays due to the gigantic explosion in the amount of molecular data. The most consuming time and space phase is the distance matrix computation. This paper addresses this issue by proposing a vectorized parallel method that accomplishes the huge number of similarity comparisons faster in less space. Performance tests on real biological datasets using core-i7 show superior results in terms of time and space.