title: Evaluation of gene ontology semantic similarities on protein interaction datasets.
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.
authors: School of Information Science and Engineering, Central South University, Changsha, People's Republic of China. gachen@csu.edu.cn
authors: Gang
authors: G
authors: Chen
authors: Jianhuang
authors: J
authors: Li
authors: Jianxin
authors: J
authors: Wang
mesh_terms: D000818:Animals; D030562:Databases, Protein; D063990:Gene Ontology; D006801:Humans; D051379:Mice; D011506:Proteins / Q000235:genetics*; D012372:ROC Curve; D051381:Rats; D012660:Semantics
chemical_list: D011506:Proteins