Human microRNA target analysis and gene ontology clustering by GOmir, a novel stand-alone application
Name
Roubelakis-2009-Human microRNA targe.pdf
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966.48 KB
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Author(s)
Roubelakis, Maria G.
Zotos, Pantelis
Papachristoudis, Georgios
Michalopoulos, Ioannis
Pappa, Kalliopi I.
Anagnou, Nicholas P.
Kossida, Sophia
Date Issued
June 2009
Journal
BMC Bioinformatics
Publisher
BioMed Central Ltd.
Citation
Roubelakis, Maria et al. “Human microRNA target analysis and gene ontology clustering by GOmir, a novel stand-alone application.” BMC Bioinformatics 10.Suppl 6 (2009): S20.
Version
Final published version
Abstract
microRNAs (miRNAs) are single-stranded RNA molecules of about 20–23 nucleotides length found in a wide variety of organisms. miRNAs regulate gene expression, by interacting with target mRNAs at specific sites in order to induce cleavage of the message or inhibit translation. Predicting or verifying mRNA targets of specific miRNAs is a difficult process of great importance.
Results
GOmir is a novel stand-alone application consisting of two separate tools: JTarget and TAGGO. JTarget integrates miRNA target prediction and functional analysis by combining the predicted target genes from TargetScan, miRanda, RNAhybrid and PicTar computational tools as well as the experimentally supported targets from TarBase and also providing a full gene description and functional analysis for each target gene. On the other hand, TAGGO application is designed to automatically group gene ontology annotations, taking advantage of the Gene Ontology (GO), in order to extract the main attributes of sets of proteins. GOmir represents a new tool incorporating two separate Java applications integrated into one stand-alone Java application.
Conclusion
GOmir (by using up to five different databases) introduces miRNA predicted targets accompanied by (a) full gene description, (b) functional analysis and (c) detailed gene ontology clustering. Additionally, a reverse search initiated by a potential target can also be conducted. GOmir can freely be downloaded BRFAA.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution
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DOI of Published Version
http://dx.doi.org/10.1186/1471-2105-10-s6-s20
