This article is part of the supplement: 22nd International Conference on Genome Informatics: Systems Biology
miR2Gene: pattern discovery of single gene, multiple genes, and pathways by enrichment analysis of their microRNA regulators
- Equal contributors
1 Department of Biomedical Informatics, Peking University Health Science Center, Beijing, 100191, China
2 MOE Key Lab of Molecular Cardiovascular Science, Peking University, Beijing, 100191, China
3 Department of Chemical Defense, Institute of Chemical Defense, 1048 Mail Box, Beijing, 102205, China
Citation and License
BMC Systems Biology 2011, 5(Suppl 2):S9 doi:10.1186/1752-0509-5-S2-S9Published: 14 December 2011
In recent years, a number of tools have been developed to explore microRNAs (miRNAs) by analyzing their target genes. However, a reverse problem, that is, inferring patterns of protein-coding genes through their miRNA regulators, has not been explored. As various miRNA annotation data become available, exploring gene patterns by analyzing the prior knowledge of their miRNA regulators is becoming more feasible.
In this study, we developed a tool, miR2Gene, for this purpose. Various sets of miRNAs, according to prior rules such as function, associated disease, tissue specificity, family, and cluster, were integrated with miR2Gene. For given genes, miR2Gene evaluates the enrichment of the predicted miRNAs that regulate them in each miRNA set. This tool can be used for single genes, multiple genes, and KEGG pathways. For the KEGG pathway, genes with enriched miRNA sets are highlighted according to various rules. We confirmed the usefulness of miR2Gene through case studies.