构建生物信息学网格计算环境

Yu-Lun Kuo, Chao-Tung Yang, Chuan-Lin Lai, Tsai-Ming Tseng
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引用次数: 7

摘要

互联网计算和网格技术有望改变我们处理复杂问题的方式。它们将使计算、数据和其他资源的大规模聚合和共享成为可能。有效地利用这些新技术将改变从高能物理学到生命科学等科学学科。生物序列的计算分析是一门计算驱动的科学。由于生物学数据的快速增长和这些数据库的异构性。我们可以利用网格系统共享和整合异构生物数据库。众所周知,生物信息学工具可以加快大规模序列数据的分析,特别是序列比对。FASTA是一种对多个蛋白质或核苷酸序列进行比对的工具。我们使用的FASTA是一个分布式并行版本。该软件使用一种称为MPl(消息传递接口)的消息传递库,可以在分布式工作站集群以及传统的并行计算机上运行。利用Globus Toolkit (GT)和SUN grid Engine (SGE)在多个Linux PC集群上提出并构建了网格计算环境。本文还介绍了该生物信息学工具在网格系统上的实验结果和性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Construct a grid computing environment for bioinformatics
Internet computing and grid technologies promise to change the way we tackle complex problems. They will enable large-scale aggregation and sharing of computational, data and other resources across institutional boundaries. And harnessing these new technologies effectively will transform scientific disciplines ranging from high-energy physics to the life sciences. The computational analysis of biological sequences is a kind of computation driven science. Cause the biology data growing quickly and these databases are heterogeneous. We can use the grid system sharing and integrating the heterogeneous biology database. As we know, bioinformatics tools can speed up analysis the large-scale sequence data, especially about sequence alignment. The FASTA is a tool for aligning multiple protein or nucleotide sequences. FASTA which we used is a distributed and parallel version. The software uses a message-passing library called MPl (Message Passing Interface) and runs on distributed workstation clusters as well as on traditional parallel computers. A grid computing environment is proposed and constructed on multiple Linux PC clusters by using Globus Toolkit (GT) and SUN Grid Engine (SGE). The experimental results and performances of the bioinformatics tool using on grid system are also presented in this paper.
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