MSAPVect: An improved MSAProbs algorithm for multi-core system

Multiple Sequence Alignment (MSA) is a basic tool for bioinformatics research and analysis. It generally constitutes the foundation of many bioinformatics studies. MSAProbs is considered the most accurate MSA tool which is based-on pair Hidden Markov Models (HMM). MSAProbs takes long runtime with the relatively increasing of sequences molecular data. Since, distance computation is the most consuming time and space stage in MSAProbs, it necessitate fast computation. In this work MSAPVect is proposed to aid in the development of MSAProbs. MSAPVect is a parallel vectorized algorithm that improves the distance matrix computing stage in MSAProbs. MSAPVect algorithm achieves the huge numbers of comparisons fast and usage less space. Comparing MSAPVect with MSAProbs demonstrates that the performance of our algorithm premium results in terms of speed and storage. The new algorithm has improvement of around 2.4-fold speedup using OpenMP library on an Intel Core-i7-3770 quad-core processor of 3.40GHz and main memory of 8GB.