Improvements in the score matrix calculation method using parallel score estimating algorithm

Abstract

<p> <b><span style="font-size:10.0pt;font-family:"">The increasing amount of sequences stored in genomic databases has become unfeasible to the sequential analysis. Then, the parallel computing brought its power to the Bioinformatics through parallel algorithms to align and analyze the sequences, providing improvements mainly in the running time of these algorithms. In many situations, the parallel strategy contributes to reducing the computational complexity of the big problems. This work shows some results obtained by an implementation of a parallel score estimating technique for the score matrix calculation stage, which is the first stage of a progressive multiple sequence alignment. The performance and quality of the parallel score estimating are compared with the results of a dynamic programming approach also implemented in parallel. This comparison shows a significant reduction of running time. Moreover, the quality of <span>the final alignment, using the new strategy, is ana</span>lyzed and compared with the quality of the approach with dynamic programming.</span></b> </p

A Greedy Clustering Algorithm for Multiple Sequence Alignment

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