BioSeek:利用源能力信息集成访问多个生物信息学数据源

Ling Liu, David J. Buttler, T. Critchlow, Wei Han, H. Paques, C. Pu, D. Rocco
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引用次数: 8

摘要

现代生物信息学数据源被分子生物学家广泛用于同源性搜索和新药发现。用户友好且响应迅速的访问是对快速增长的异构和分布式数据源集合进行集成访问的最理想的属性之一。与生物信息学相关的数字信息(如基因组、蛋白质序列、蛋白质结构等)的数量和多样性的增加导致了传统数据管理系统所没有的一个日益严重的问题,即从许多候选选择中找出哪些信息源是最相关和最容易获得的,以回答给定的用户查询。我们把这个问题称为查询路由问题。本文介绍了查询路由的概念和问题,提出了一种基于多级渐进式剪枝策略的可扩展查询路由系统的设计方案。关键思想是独立地创建和维护源能力配置文件,并提供能够通过智能地使用源配置文件动态地发现给定查询的相关信息源的算法。与大多数搜索引擎和软件采用的基于关键字的索引技术相比,我们的方法提供了细粒度的兴趣匹配,因此在处理复杂条件的查询时更加强大和有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
BioSeek: exploiting source-capability information for integrated access to multiple bioinformatics data sources
Modern Bioinformatics data sources are widely used by molecular biologists for homology searching and new drug discovery. User-friendly and yet responsive access is one of the most desirable properties for integrated access to the rapidly growing, heterogeneous, and distributed collection of data sources. The increasing volume and diversity of digital information related to bioinformatics (such as genomes, protein sequences, protein structures, etc.) have led to a growing problem that conventional data management systems do not have, namely finding which information sources out of many candidate choices are the most relevant and most accessible to answer a given user query. We refer to this problem as the query routing problem. In this paper we introduce the notation and issues of query routing, and present a practical solution for designing a scalable query routing system based on multi-level progressive pruning strategies. The key idea is to create and maintain source capability profiles independently, and to provide algorithms that can dynamically discover relevant information sources for a given query through the smart use of source profiles. Compared to the keyword-based indexing techniques adopted in most of the search engines and software, our approach offers fine-granularity of interest matching, thus it is more powerful and effective for handling queries with complex conditions.
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