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A measure of semantic similarity between gene ontology terms based on semantic pathway covering

机译:基于语义路径覆盖的基因本体术语之间语义相似度的度量

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摘要

Semantic similarity between Gene Ontology (GO) terms is critical in resolving semantic heterogeneousness when integrating heterogeneous biological databases. Traditionally, distance based and information content based measures are two major methods. In this paper, a new method based on semantic pathway covering is proposed and an algorithm, COMBINE algorithm, is presented, which considers information contents of two given nodes and those of all nodes included in the two nodes' pathways. Experiments show that COMBINE algorithm obtains the highest correlation index compared with those distance based and information content based algorithms .
机译:在集成异构生物数据库时,基因本体(GO)术语之间的语义相似性对于解决语义异构性至关重要。传统上,基于距离和基于信息内容的度量是两种主要方法。本文提出了一种基于语义路径覆盖的新方法,提出了一种考虑了两个给定节点以及两个节点路径中包括的所有节点的信息内容的COMBINE算法。实验表明,与基于距离和基于信息内容的算法相比,COMBINE算法获得了最高的相关指数。

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