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 http://mlg.hit.edu.cn:8082/.
|Journal||BMC Systems Biology|
|State||Published - Dec 12 2014|
Bibliographical noteFunding 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.
© 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