GRtoGR: A system for mapping go relations to gene relations

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We introduce in this paper a biological search engine called GRtoGR. Given a set S of 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.

Original languageBritish English
Article number3
Pages (from-to)289-297
Number of pages9
JournalIEEE Transactions on Nanobioscience
Issue number4
StatePublished - Dec 2013


  • Biological search engine
  • Gene Ontology
  • GO term
  • Related genes
  • Related terms
  • Semantic similarity


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