An integrative approach for measuring semantic similarities using gene ontology

Jiajie Peng, Hongxiang Li, Qinghua Jiang, Yadong Wang, Jin Chen

Research output: Contribution to journalArticlepeer-review

20 Scopus citations


Background: Gene Ontology (GO) provides rich information and a convenient way to study gene functional similarity, which has been successfully used in various applications. However, the existing GO based similarity measurements have limited functions for only a subset of GO information is considered in each measure. An appropriate integration of the existing measures to take into account more information in GO is demanding. Results: We propose a novel integrative measure called InteGO 2 to automatically select appropriate seed measures and then to integrate them using a metaheuristic search method. The experiment results show that InteGO 2 significantly improves the performance of gene similarity in human, Arabidopsis and yeast on both molecular function and biological process GO categories. Conclusions: InteGO 2 computes gene-to-gene similarities more accurately than tested existing measures and has high robustness. The supplementary document and software are available at

Original languageEnglish
Article numberS8
JournalBMC Systems Biology
Issue number5
StatePublished - Dec 12 2014

Bibliographical note

Funding Information:
This project has been funded by the U.S. Department of Energy, grant no. DE-FG02-91ER20021 to J.C; the National High Technology Research and Development Program of China grant (no. 2012AA020404 and 2012AA02A602) and the National Natural Science Foundation of China grant (no. 61173085) to Y. W.

Publisher Copyright:
© 2014 Peng et al.


  • Gene ontology
  • Integrative approach
  • Semantic similarity

ASJC Scopus subject areas

  • Structural Biology
  • Modeling and Simulation
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics


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