基于混合并行计算的多序列比对

Elói Araújo, M. A. Stefanes, Valter de O. Ferlete, L. Rozante
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引用次数: 2

摘要

多序列比对(MSA)在几个科学领域,特别是在生物信息学领域是至关重要的。MSA在表达方面取得了很大进展,并为此提出了许多方法、算法和工具。由于MSA是一个np困难问题,人们的努力导致了启发式方法的出现来解决它。最近,基于渐进式对齐的启发式算法由于对齐的质量和相对较好的性能而受到重视。尽管取得了重大进展,但MSA仍然是一项耗时的任务,并且已经研究了并行解决方案。提出了一种基于gpu集群的渐进对齐求解MSA的新算法。我们的实验结果显示,对于包含长度在60到10k之间的序列的实例,加速效果令人鼓舞。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiple Sequence Alignment using Hybrid Parallel Computing
Multiple sequence alignment (MSA) is critical in several areas of science, especially in bioinformatics. Expressive advances have been developed in MSA and many methods, algorithms and tools have been proposed for it. Since the MSA is an NP-hard problem, efforts have led to the emergence of heuristics to solve it. More recently, heuristics based on progressive alignment have highlighted due to the quality of the alignment and relatively good performance. Despite significant advances, MSA remains a time-consuming task and parallel solutions have been investigated. We propose a novel algorithm for solving MSA based on progressive alignment using cluster of GPUs. Our experimental results showed encouraging speedups for instances containing sequences ranging in length between 60 and 10k.
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