Accurate microRNA target prediction correlates with protein repression levels

Maragkakis, M; Alexiou, P; Papadopoulos, GL; Reczko, M; Dalamagas, T; Giannopoulos, G; Goumas, G; Koukis, E; Kourtis, K; Simossis, VA; Sethupathy, P; Vergoulis, T; Koziris, N; Sellis, T; Tsanakas, P; Hatzigeorgiou, AG

dc.contributor.author	Maragkakis, M	en
dc.contributor.author	Alexiou, P	en
dc.contributor.author	Papadopoulos, GL	en
dc.contributor.author	Reczko, M	en
dc.contributor.author	Dalamagas, T	en
dc.contributor.author	Giannopoulos, G	en
dc.contributor.author	Goumas, G	en
dc.contributor.author	Koukis, E	en
dc.contributor.author	Kourtis, K	en
dc.contributor.author	Simossis, VA	en
dc.contributor.author	Sethupathy, P	en
dc.contributor.author	Vergoulis, T	en
dc.contributor.author	Koziris, N	en
dc.contributor.author	Sellis, T	en
dc.contributor.author	Tsanakas, P	en
dc.contributor.author	Hatzigeorgiou, AG	en
dc.date.accessioned	2014-03-01T01:29:47Z
dc.date.available	2014-03-01T01:29:47Z
dc.date.issued	2009	en
dc.identifier.issn	1471-2105	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/19342
dc.subject	Gene Expression	en
dc.subject	Messenger Rna	en
dc.subject	microrna	en
dc.subject	non-coding rna	en
dc.subject	Signal To Noise Ratio	en
dc.subject	Fold Change	en
dc.subject	False Positive Rate	en
dc.subject.classification	Biochemical Research Methods	en
dc.subject.classification	Biotechnology & Applied Microbiology	en
dc.subject.classification	Mathematical & Computational Biology	en
dc.subject.other	microRNA	en
dc.subject.other	protein	en
dc.subject.other	accuracy	en
dc.subject.other	analytical error	en
dc.subject.other	article	en
dc.subject.other	controlled study	en
dc.subject.other	gene identification	en
dc.subject.other	gene targeting	en
dc.subject.other	genetic algorithm	en
dc.subject.other	genetic conservation	en
dc.subject.other	online system	en
dc.subject.other	prediction	en
dc.subject.other	protein folding	en
dc.subject.other	RNA analysis	en
dc.subject.other	signal noise ratio	en
dc.subject.other	Algorithms	en
dc.subject.other	Binding Sites	en
dc.subject.other	Computational Biology	en
dc.subject.other	MicroRNAs	en
dc.subject.other	Proteins	en
dc.subject.other	Sequence Analysis, RNA	en
dc.title	Accurate microRNA target prediction correlates with protein repression levels	en
heal.type	journalArticle	en
heal.identifier.primary	10.1186/1471-2105-10-295	en
heal.identifier.secondary	http://dx.doi.org/10.1186/1471-2105-10-295	en
heal.identifier.secondary	1471	en
heal.language	English	en
heal.publicationDate	2009	en
heal.abstract	Background: MicroRNAs are small endogenously expressed non-coding RNA molecules that regulate target gene expression through translation repression or messenger RNA degradation. MicroRNA regulation is performed through pairing of the microRNA to sites in the messenger RNA of protein coding genes. Since experimental identification of miRNA target genes poses difficulties, computational microRNA target prediction is one of the key means in deciphering the role of microRNAs in development and disease. Results: DIANA-microT 3.0 is an algorithm for microRNA target prediction which is based on several parameters calculated individually for each microRNA and combines conserved and non-conserved microRNA recognition elements into a final prediction score, which correlates with protein production fold change. Specifically, for each predicted interaction the program reports a signal to noise ratio and a precision score which can be used as an indication of the false positive rate of the prediction. Conclusion: Recently, several computational target prediction programs were benchmarked based on a set of microRNA target genes identified by the pSILAC method. In this assessment DIANA-microT 3.0 was found to achieve the highest precision among the most widely used microRNA target prediction programs reaching approximately 66%. The DIANA-microT 3.0 prediction results are available online in a user friendly web server at http://www.microrna.gr/microT. © 2009 Maragkakis et al; licensee BioMed Central Ltd.	en
heal.publisher	BIOMED CENTRAL LTD	en
heal.journalName	BMC Bioinformatics	en
dc.identifier.doi	10.1186/1471-2105-10-295	en
dc.identifier.isi	ISI:000270276500001	en
dc.identifier.volume	10	en
dc.identifier.spage	295	en