Title: Evaluation of gene ontology semantic similarities on protein interaction datasets

Authors: Gang Chen; Jianhuang Li; Jianxin Wang

Addresses: School of Information Science and Engineering, Central South University, Changsha, P.R. China ' Department of Oncology, Xiangya Hospital, Central South University, Changsha, P.R. China ' School of Information Science and Engineering, Central South University, Changsha, P.R. China

Abstract: Background - Because of the importance of protein interactions in organisms, researchers are interested in the functional similarity between interacted proteins. Gene ontology semantic similarity provides a novel way to measure the similarity between gene products, including proteins. Various methods have been proposed for calculating the semantic similarity between GO terms and gene products, therefore evaluating these measurements on protein interaction data is helpful and necessary for related studies. Results - 35 different definitions of GO semantic similarity are evaluated by receiver operating characteristic analysis, information gain and Chi-square on core PPIs of four organisms, human, rat, mouse and fruit fly, from DIP database. Conclusions - For the identification of interacted proteins, CoutoEnriched is the best definition of the similarity between GO terms, and there is no significant difference between most methods calculating the semantic similarity between two sets of GO terms.

Keywords: bioinformatics; gene ontology; semantic similarity; protein interaction networks; protein interactions; proteins.

DOI: 10.1504/IJBRA.2013.052448

International Journal of Bioinformatics Research and Applications, 2013 Vol.9 No.2, pp.173 - 183

Received: 21 Jun 2011
Accepted: 13 Jul 2011
Published online: 06 Sep 2014 *

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