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Construct a grid computing environment for bioinformatics

机译:为生物信息学构建网格计算环境

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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.
机译:互联网计算和网格技术有望改变我们解决复杂问题的方式。它们将使跨机构边界的计算,数据和其他资源的大规模聚合和共享成为可能。有效利用这些新技术将改变从高能物理到生命科学的科学学科。生物序列的计算分析是一种计算驱动的科学。导致生物学数据快速增长,并且这些数据库是异构的。我们可以使用网格系统共享和集成异构生物学数据库。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速度,尤其是在序列比对方面。 FASTA是用于比对多个蛋白质或核苷酸序列的工具。我们使用的FASTA是分布式和并行版本。该软件使用称为MP1(消息传递接口)的消息传递库,并在分布式工作站集群以及传统的并行计算机上运行。通过使用Globus Toolkit(GT)和SUN Grid Engine(SGE),提出并在多个Linux PC群集上构建了网格计算环境。本文还介绍了基于网格系统的生物信息学工具的实验结果和性能。

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