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

机译:使用并行分数估计算法的分数矩阵计算方法的改进

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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 the final alignment, using the new strategy, is analyzed and compared with the quality of the approach with dynamic programming.
机译:存储在基因组数据库中的序列数量越来越大,对于顺序分析已经变得不可行。然后,并行计算通过并行算法来比对和分析序列,从而为生物信息学提供了强大的功能,主要是在这些算法的运行时间方面提供了改进。在许多情况下,并行策略有助于降低大问题的计算复杂性。这项工作显示了通过对分数矩阵计算阶段(这是渐进多序列比对的第一阶段)的并行分数估计技术的实施而获得的一些结果。将并行分数估计的性能和质量与也并行实现的动态编程方法的结果进行比较。该比较显示运行时间大大减少。此外,使用新策略对最终比对的质量进行了分析,并与动态编程方法的质量进行了比较。

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