Parallel Phylogenetic Inference

Q. Snell, M. Whiting, M. Clement, David McLaughlin
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引用次数: 15

Abstract

Recent advances in DNA sequencing technology have created large data sets upon which phylogenetic inference can be performed. However, current research is limited by the prohibitive time necessary to perform tree search on even a reasonably sized data set. Some parallel algorithms have been developed but the biological research community does not use them because they don’t trust the results from newly developed parallel software. This paper presents a new phylogenetic algorithm that allows existing, trusted phylogenetic software packages to be executed in parallel using the DOGMA parallel processing system. The results presented here indicate that data sets that currently take as much as 11 months to search using current algorithms, can be searched in as little as 2 hours using as few as 8 processors. This reduction in the time necessary to complete a phylogenetic search allows new research questions to be explored in many of the biological sciences.
平行系统发育推断
DNA测序技术的最新进展创造了大量的数据集,在这些数据集上可以进行系统发育推断。然而,当前的研究受限于在合理大小的数据集上执行树搜索所需的时间限制。一些并行算法已经被开发出来,但生物研究界并没有使用它们,因为他们不相信新开发的并行软件的结果。本文提出了一种新的系统发育算法,该算法允许现有的、可信的系统发育软件包使用DOGMA并行处理系统并行执行。这里展示的结果表明,目前使用现有算法需要11个月才能搜索到的数据集,使用8个处理器就可以在短短2小时内搜索到。完成系统发育研究所需时间的减少,使许多生物科学领域的新研究问题得以探索。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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