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

G. F. D. Zafalon, E. A. Marucci, J. C. Momente, J. Amazonas, L. Sato, J. M. Machado
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引用次数: 6

Abstract

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.
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改进了基于并行分数估计算法的分数矩阵计算方法
基因组数据库中存储的序列数量不断增加,使序列分析变得不可行。然后,并行计算通过并行算法将其能力引入生物信息学,对序列进行对齐和分析,主要在这些算法的运行时间上提供改进。在许多情况下,并行策略有助于降低大问题的计算复杂度。这项工作展示了通过在分数矩阵计算阶段实现并行分数估计技术获得的一些结果,这是渐进多序列比对的第一阶段。将该方法的性能和质量与同样并行实现的动态规划方法的结果进行了比较。这个比较显示了运行时间的显著减少。此外,还对采用新策略的最终对齐质量进行了分析,并与采用动态规划方法的对齐质量进行了比较。
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