Geodesic
An Integrated Information-Based Similarity Measurement of Gene Ontology Terms
Computer Science and Information Systems, Tome 12 (2015) no. 4.

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Measuring the semantic similarity between pairs of terms in Gene Ontology (GO) can help to compare genes that can not be compared by other computational methods. In this study, we proposed an integrated information-based similarity measurement (IISM) to calculate the semantic similarity between two GO terms by taking into account multiple common ancestors that they share, and aggregating the semantic information and depth information of the non-redundant common ancestors. Our method searches for non-redundant common ancestors in an effective way. Validation experiments were conducted on both gene expression dataset and pathway dataset, and the experimental results suggest the superiority of our method against some existing methods.
Keywords: Gene Ontology, GO terms, semantic similarity, biological pathways, gene expression profile 
@article{CSIS_2015_12_4_a7,
     author = {Shu-Bo Zhang and Jian-Huang Lai},
     title = {An {Integrated} {Information-Based} {Similarity} {Measurement} of {Gene} {Ontology} {Terms}},
     journal = {Computer Science and Information Systems},
     publisher = {mathdoc},
     volume = {12},
     number = {4},
     year = {2015},
     url = {http://geodesic.mathdoc.fr/item/CSIS_2015_12_4_a7/}
}
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Shu-Bo Zhang; Jian-Huang Lai. An Integrated Information-Based Similarity Measurement of Gene Ontology Terms. Computer Science and Information Systems, Tome 12 (2015) no. 4. http://geodesic.mathdoc.fr/item/CSIS_2015_12_4_a7/