Fast Structural Similarity Search Based on Topology String Matching

Sung-Hee Park, D. Gilbert, K. Ryu
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引用次数: 1

Abstract

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.
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基于拓扑字符串匹配的快速结构相似性搜索
利用空间数据类型表示蛋白质的几何形状,描述了蛋白质结构的抽象数据模型,并提出了一种基于拓扑字符串匹配的快速结构相似性搜索框架。该系统是在Oracle 9i空间数据库管理系统之上实现的。对来自Chew和Kedem数据集的36种蛋白质以及PDB40的一个子集进行了性能评估。我们的方法在匹配质量方面表现良好,同时具有执行速度快和在多项式时间内计算相似度搜索的优点。因此,本研究表明,利用空间数据库管理系统的空间关系预先计算二级结构元素之间拓扑属性的字符串表示对于快速结构相似性搜索是可行的。
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