BioGridPSE:使用计算和数据网格的生物信息学分析集成解决方案

Choong-Hyun Sun, Youngwoong Han, Minseong Kim, G. Yi
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引用次数: 1

摘要

生物信息学领域面临着数据的指数增长和问题复杂性的增加。计算和数据网格的最新进展是处理这些情况的一种方法。网格计算资源的简化使用和生物信息学分析中大数据放置的容错性是利用网格技术的主要关键。为了实现网格计算任务,我们已经提供了一个基于网格支持过程管理器的集成生物信息学解决方案的问题解决环境模型。在这里,我们还开发了BioGrid问题解决环境(BioGridPSE)作为更新版本,保证在网格中完成计算作业和数据放置作业,并支持灵活的生物信息学分析过程设计,用户自定义界面生成和可编程数据解析。BioGridPSE的效率和可用性已经通过高通量和复杂的生物信息学分析(如全基因组全球比对)进行了测试
本文章由计算机程序翻译,如有差异,请以英文原文为准。
BioGridPSE: Integrated Solution for Bioinformatics Analysis Using Computing and Data Grid
The bioinformatics field confronts exponential growth of data and increasing problem complexity. Recent progress in computing and data grid are highlighted as an approach to handle these situations. The simplified usage of grid computing resources and the fault-tolerance of large data placement in bioinformatics analysis are the main keys for taking advantage of grid technology. For the purpose of achieving grid computing jobs, we have already provided a model of problem solving environment for integrated bioinformatics solution on grid supporting process manager. Here we have additionally developed BioGrid problem solving environment (BioGridPSE) as an updated version that guarantees both the completion of computational jobs and data placement jobs in the grid and supports flexible process design for bioinformatics analysis, user customized interface generation, and programmable data parsing. The efficiency and usability of BioGridPSE have been tested with high-throughput and complex bioinformatics analysis such as whole genome global alignment
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