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FAST STRUCTURAL SIMILARITY SEARCH BASED ON TOPOLOGY STRING MATCHING

机译:基于拓扑字符串匹配的快速结构相似性搜索

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We describe an abstract data model of protein structures by representing the geometry of proteins using spatial data types and present a framework for fast structural similarity search based on the matching of topology strings using bipartite graph matching. The system has been implemented on top of the Oracle 9i spatial database management system. The performance evaluation was conducted on 36 proteins from the Chew and Kedem data set and also on a subset of the PDB40. Our method performs well in terms of the quality of matching whilst having the advantage of fast execution and being able to compute similarity search in polynomial time. Thus, this work shows that the pre-computed string representation of topological properties between secondary structure elements using spatial relationships of spatial database management system is practical for fast structural similarity search.
机译:我们通过使用空间数据类型代表蛋白质的几何形状来描述蛋白质结构的抽象数据模型,并基于使用双标图匹配的拓扑字符串的匹配来提供快速结构相似性搜索的框架。系统已在Oracle 9i空间数据库管理系统之上实现。性能评估在来自咀嚼和KEDEM数据集的36个蛋白质上进行,并且还在PDB40的子集上进行。我们的方法在具有快速执行的优点并且能够计算多项式时间中的相似性搜索的情况下,我们的方法在匹配的质量方面表现良好。因此,该作业表明,使用空间数据库管理系统的空间关系的二次结构元件之间的拓扑结构的预计算串表示对于快速结构相似性搜索是实用的。

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