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GORank: Semantic Similarity Search for Gene Products using Gene Ontology  

Kim, Ki-Sung (서울대학교 전기컴퓨터공학부)
Yoo, Sang-Won (서울대학교 전기컴퓨터공학부)
Kim, Hyoung-Joo (서울대학교 전기컴퓨터공학부)
Publication Information
Journal of KIISE:Databases / v.33, no.7, 2006 , pp. 682-692 More about this Journal
Abstract
Searching for gene products which have similar biological functions are crucial for bioinformatics. Modern day biological databases provide the functional description of gene products using Gene Ontology(GO). In this paper, we propose a technique for semantic similarity search for gene products using the GO annotation information. For this purpose, an information-theoretic measure for semantic similarity between gene products is defined. And an algorithm for semantic similarity search using this measure is proposed. We adapt Fagin's Threshold Algorithm to process the semantic similarity query as follows. First, we redefine the threshold for our measure. This is because our similarity function is not monotonic. Then cluster-skipping and the access ordering of the inverted index lists are proposed to reduce the number of disk accesses. Experiments with real GO and annotation data show that GORank is efficient and scalable.
Keywords
Gene Ontology; Semantic similarity search;
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