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dc.contributor.authorRoubelakis, Maria G.en_US
dc.contributor.authorZotos, Pantelisen_US
dc.contributor.authorPapachristoudis, Georgiosen_US
dc.contributor.authorMichalopoulos, Ioannisen_US
dc.contributor.authorPappa, Kalliopi I.en_US
dc.contributor.authorAnagnou, Nicholas P.en_US
dc.contributor.authorKossida, Sophiaen_US
dc.date.accessioned2009-10-19T13:35:29Z
dc.date.available2009-10-19T13:35:29Z
dc.date.issued2009-06en_US
dc.identifier.issn1471-2105en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/49470
dc.description.abstractBackground: 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.en_US
dc.language.isoen_USen_US
dc.publisherBioMed Central Ltd.en_US
dc.relation.isversionofhttp://dx.doi.org/10.1186/1471-2105-10-S6-S20en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttp://creativecommons.org/licenses/by/2.0en_US
dc.sourcePublisheren_US
dc.titleHuman microRNA target analysis and gene ontology clustering by GOmir, a novel stand-alone applicationen_US
dc.typeArticleen_US
dc.identifier.citationRoubelakis, Maria, Pantelis Zotos, Georgios Papachristoudis, Ioannis Michalopoulos, Kalliopi Pappa, Nicholas Anagnou, and Sophia Kossida. 2009. Human microRNA target analysis and gene ontology clustering by GOmir, a novel stand-alone application. BMC Bioinformatics 10, no. Suppl 6: S20.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.approverPapachristoudis, Georgiosen_US
dc.contributor.mitauthorPapachristoudis, Georgiosen_US
dc.relation.journalBMC Bioinformaticsen_US
dc.eprint.versionFinal published versionen_US
dc.identifier.pmid19534746en_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsRoubelakis, Maria G; Zotos, Pantelis; Papachristoudis, Georgios; Michalopoulos, Ioannis; Pappa, Kalliopi I; Anagnou, Nicholas P; Kossida, Sophiaen
mit.licensePUBLISHER_CCen_US
mit.metadata.statusComplete


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