| Literature DB >> 23955781 |
Abstract
We introduce in this paper a biological search engine called GRtoGR. Given a set of S genes, GRtoGR would determine from GO graph the most significant Lowest Common Ancestor (LCA) of the GO terms annotating the set S. This significant LCA annotates the genes that are the most semantically related to the set S. The framework of GRtoGR refines the concept of LCA by introducing the concepts of Relevant Lowest Common Ancestor (RLCA) and Semantically Relevant Lowest Common Ancestor (SRLCA). A SRLCA is the most significant LCA of the GO terms annotating the set S. We observe that the existence of the GO terms annotating the set S is dependent on the existence of this SRLCA in GO graph. That is, the terms annotating a given set of genes usually have existence dependency relationships with the SRLCA of these terms. We evaluated GRtoGR experimentally and compared it with nine other methods. Results showed marked improvement.Entities:
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Year: 2013 PMID: 23955781 DOI: 10.1109/TNB.2013.2278480
Source DB: PubMed Journal: IEEE Trans Nanobioscience ISSN: 1536-1241 Impact factor: 2.935