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Supporting High Performance Bioinformatics Flat-File Data Processing Using Indices

机译:支持高性能生物信息学使用索引的平面文件数据处理

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As an essential part of in vitro analysis, biological database query has become more and more important in the research process. A few challenges that are specific to bioinformatics applications are data heterogeneity, large data volume and exponential data growth, constant appearance of new data types and data formats. We have developed an integration system that processes data in their flat file formats. Its advantages include the reduction of overhead and programming efforts. In the paper, we discuss the usage of indicing techniques on top of this flat file query system. Besides the advantage of processing flat files directly, the system also improves its performance and functionality by using indexes. Experiments based on real life queries are used to test the integration system.
机译:作为体外分析的重要组成部分,生物数据库查询在研究过程中变得越来越重要。一些特定于生物信息学应用的挑战是数据异质性,大数据量和指数数据增长,新数据类型的常量外观和数据格式。我们开发了一个集成系统,以其平面文件格式处理数据。其优势包括减少开销和编程努力。在论文中,我们讨论了在此平面文件查询系统之上的指示技术的使用。除了直接处理平面文件的优势外,系统还通过使用索引来提高其性能和功能。基于现实生活查询的实验用于测试集成系统。

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