Nucleic Acids Research Advance Access originally published online on October 16, 2007
Nucleic Acids Research 2008 36(Database issue):D159-D164; doi:10.1093/nar/gkm829
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Nucleic Acids Research, 2008, Vol. 36, Database issue D159-D164
© 2007 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
This article appears in the following Nucleic Acids Research issue: Database issue [View the issue table of contents]
Articles |
miRGator: an integrated system for functional annotation of microRNAs
1Division of Life and Pharmaceutical Sciences, Ewha Womans University, Seoul 120-750, 2Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 151-742 and 3Department of Chemistry, Seoul National University, Seoul 151-742, Korea
* To whom correspondence should be addressed. Tel: +82 2 3277 2888; Fax: +82 2 3277 3760; Email: sanghyuk{at}ewha.ac.kr
Received August 15, 2007. Revised September 19, 2007. Accepted September 20, 2007.
MicroRNAs (miRNAs) constitute an important class of regulators that are involved in various cellular and disease processes. However, the functional significance of each miRNA is mostly unknown due to the difficulty in identifying target genes and the lack of genome-wide expression data combining miRNAs, mRNAs and proteins. We introduce a novel database, miRGator, that integrates the target prediction, functional analysis, gene expression data and genome annotation. MiRNA function is inferred from the list of target genes predicted by miRanda, PicTar and TargetScanS programs. Statistical enrichment test of target genes in each term is performed for gene ontology, pathway and disease annotations. Associated terms may provide valuable insights for the function of each miRNA. For the expression analysis, miRGator integrates public expression data of miRNA with those of mRNA and protein. Expression correlation between miRNA and target mRNA/proteins is evaluated and their expression patterns can be readily compared. Our web implementation supports diverse query types including miRNA name, gene symbol, gene ontology, pathway and disease terms. Interfaces for exploring common targets or regulatory miRNAs and for profiling compendium expression data have been developed as well. Currently, miRGator, available at: http://genome.ewha.ac.kr/miRGator/, supports the human and mouse genomes.
The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.
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