Identifying cross-category relations in gene ontology and constructing genome-specific term association networks

BMC Bioinformatics

Proceedings

Jin Chen¹  Yadong Wang²  Jiajie Peng³ 

[1] MSU-DOE Plant Research Laboratory, Michigan State University, 48824, East Lansing, MI, USA;Department of Computer Science and Engineering, Michigan State University, 48824, East Lansing, MI, USA;School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China;School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China;MSU-DOE Plant Research Laboratory, Michigan State University, 48824, East Lansing, MI, USA;

关键词: Gene Ontology;    Association Network;    Vector Space Model;    Term Relationship;    Enzyme Commission Number;   

DOI  :  10.1186/1471-2105-14-S2-S15

来源: Springer

【 摘 要 】

BackgroundGene Ontology (GO) has been widely used in biological databases, annotation projects, and computational analyses. Although the three GO categories are structured as independent ontologies, the biological relationships across the categories are not negligible for biological reasoning and knowledge integration. However, the existing cross-category ontology term similarity measures are either developed by utilizing the GO data only or based on manually curated term name similarities, ignoring the fact that GO is evolving quickly and the gene annotations are far from complete.ResultsIn this paper we introduce a new cross-category similarity measurement called CroGO by incorporating genome-specific gene co-function network data. The performance study showed that our measurement outperforms the existing algorithms. We also generated genome-specific term association networks for yeast and human. An enrichment based test showed our networks are better than those generated by the other measures.ConclusionsThe genome-specific term association networks constructed using CroGO provided a platform to enable a more consistent use of GO. In the networks, the frequently occurred MF-centered hub indicates that a molecular function may be shared by different genes in multiple biological processes, or a set of genes with the same functions may participate in distinct biological processes. And common subgraphs in multiple organisms also revealed conserved GO term relationships. Software and data are available online at http://www.msu.edu/~jinchen/CroGO.

【 授权许可】

Unknown   
© Peng et al.; licensee BioMed Central Ltd. 2013. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.