期刊
BMC BIOINFORMATICS
卷 19, 期 -, 页码 -出版社
BMC
DOI: 10.1186/s12859-018-2251-x
关键词
Disease gene; Inflammatory bowel disease; Gene expression; Protein-protein interaction
类别
资金
- NAIST Global Collaborative Program
- Ministry of Education, Culture, Sports, Science, and Technology of Japan [16K07223, 17K00406]
- Research Manitoba, Health Sciences Centre Foundation
- Mitacs of Canada
- Grants-in-Aid for Scientific Research [17K00406, 16K07223] Funding Source: KAKEN
Background: There are different and complicated associations between genes and diseases. Finding the causal associations between genes and specific diseases is still challenging. In this work we present a method to predict novel associations of genes and pathways with inflammatory bowel disease (IBD) by integrating information of differential gene expression, protein-protein interaction and known disease genes related to IBD. Results: We downloaded IBD gene expression data from NCBI's Gene Expression Omnibus, performed statistical analysis to determine differentially expressed genes, collected known IBD genes from DisGeNet database, which were used to construct a IBD related PPI network with HIPPIE database. We adapted our graph-based clustering algorithm DPCIusO to cluster the disease PPI network. We evaluated the statistical significance of the identified clusters in the context of determining the richness of IBD genes using Fisher's exact test and predicted novel genes related to IBD. We showed 93.8% of our predictions are correct in the context of other databases and published literatures related to IBD. Conclusions: Finding disease-causing genes is necessary for developing drugs with synergistic effect targeting many genes simultaneously. Here we present an approach to identify novel disease genes and pathways and discuss our approach in the context of IBD. The approach can be generalized to find disease-associated genes for other diseases.
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