基于OpenMP和分区方案的并行快速动态序列比对算法

Sara Shehab
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引用次数: 0

摘要

序列比对是生物信息学中最重要的工作之一。有两种类型的成对比对和多序列比对。许多算法被提出来完成这个任务。这些算法的关键参数是对齐及其评分值。如果所提出的算法使分数最大化,那么它就是最优的。用于排列序列的算法有两个主要缺点。首先是灵敏度,当使用的数据量很大时,输出分数不是最优的,灵敏度很差。二是数据量大时的执行时间。为了克服这两个问题,提出了并行版的快速动态配对序列比对算法。第一个问题通过分区方案解决,第二个问题通过使用OpenMP在可用线程上分配任务解决。结果表明,所提出的并行算法具有较高的精度和灵敏度,并缩短了执行时间。关键词:序列比对,最优评分,成对序列比对快速动态算法,OpenMP
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parallel Fast Dynamic Algorithm for Sequence Alignment Using OpenMP and Partitioning Scheme
Sequence alignment process considered one of the most important tasks in bioinformatic. There are two types of alignment pairwise and multiple sequence alignment. Many algorithms proposed to complete this task. The key parameter in these algorithms is alignment and its scoring value. If the proposed algorithm maximizes the score, so it will be optimal. The algorithms used to align sequences have two main drawbacks. The first is the sensitivity when the data used is very large, the output score is not optimal and has a bad sensitivity. The second is the execution time when the data is large. To overcome these two problems the parallel version of Fast Dynamic Algorithm for Pairwise sequence Alignment is proposed. The first problem solved by partitioning scheme and the second solved by using OpenMP to distribute tasks on available threads. The results indicated that the proposed parallel Algorithms achieve high level of accuracy and sensitivity and improve the execution time. Keywords—Sequence alignment, optimal score, Fast Dynamic Algorithm for Pairwise Sequence Alignment, OpenMP
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