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On Construction of Cluster and Grid Computing Platforms for Parallel Bioinformatics Applications

机译:关于并行生物信息学应用的集群和网格计算平台的构建

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Biology databases are diverse and massive. As a result, researchers must compare each sequence with vast numbers of other sequences. Comparison, whether of structural features or protein sequences, is vital in bioinformatics. These activities require high-speed, high-performance computing power to search through and analyze large amounts of data and industrial-strength databases to perform a range of data-intensive computing functions. Grid computing and Cluster computing meet these requirements. Biological data exist in various web services that help biologists search for and extract useful information. The data formats produced are heterogeneous and powerful tools are needed to handle the complex and difficult task of integrating the data. This paper presents a review of the technologies and an approach to solve this problem using cluster and grid computing technologies. The authors implement an experimental distributed computing application for bioinformatics, consisting of basic high-performance computing environments (Grid and PC Cluster systems), multiple interfaces at user portals that provide useful graphical interfaces to enable biologists to benefit directly from the use of high-performance technology, and a translation tool for converting biology data into XML format.
机译:生物学数据库是多种多样的。结果,研究人员必须将每个序列与大量其他序列进行比较。无论是结构特征还是蛋白质序列的比较,在生物信息学中都是至关重要的。这些活动需要高速,高性能的计算能力来搜索和分析大量数据以及具有行业实力的数据库,以执行一系列数据密集型计算功能。网格计算和群集计算满足这些要求。各种网络服务中都存在生物数据,这些数据可帮助生物学家搜索和提取有用的信息。产生的数据格式是异构的,并且需要强大的工具来处理集成数据的复杂而困难的任务。本文介绍了该技术的概述以及使用集群和网格计算技术解决此问题的方法。作者实现了用于生物信息学的实验性分布式计算应用程序,该应用程序由基本的高性能计算环境(网格和PC群集系统),用户门户上的多个界面组成,这些界面提供有用的图形界面,使生物学家可以直接从高性能的使用中受益技术,以及将生物学数据转换为XML格式的翻译工具。

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