DIANA-microT web server: elucidating microRNA functions through target prediction

By Manolis Maragkakis, Martin Reczko, Victor A. Simossis, Panagiotis Alexiou, Giorgos L. Papadopoulos, Theodore Dalamagas, G. Giannopoulos, G. Goumas, Evangelos Koukis, K. Kourtis and 5 more. Nucleic Acids Res., 2009

369 citations recorded by the source corpus.

Computational microRNA (miRNA) target prediction is one of the key means for deciphering the role of miRNAs in development and disease. Here, we present the DIANA-microT web server as the user interface to the DIANA-microT 3.0 miRNA target prediction algorithm. The web server provides extensive information for predicted miRNA:target gene interactions with a user-friendly interface, providing extensive connectivity to online biological resources. Target gene and miRNA functions may be elucidated through automated bibliographic searches and functional information is accessible through Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The web server offers links to nomenclature, sequence and protein databases, and users are facilitated by being able to search for targeted genes using different nomenclatures or functional features, such as the genes possible involvement in biological pathways. The target prediction algorithm supports parameters calculated individually for each miRNA:target gene interaction and provides a signal-to-noise ratio and a precision score that helps in the evaluation of the significance of the predicted results. Using a set of miRNA targets recently identified through the pSILAC method, the performance of several computational target prediction programs was assessed. DIANA-microT 3.0 achieved there with 66% the highest ratio of correctly predicted targets over all predicted targets. The DIANA-microT web server is freely available at www.microrna.gr/microT.

Subfields: Cancer Research, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/f8a6d71ade5db33e579fff7d5ebe86e2045d44ff

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cancer Research

In Molecular Biology

Citations in the corpus

miRWalk - Database: Prediction of possible miRNA binding sites by "walking" the genes of three genomes (2011, neutral): “In the past years, a large number of target prediction programs and databases on experimentally validated information have been developed for animal miRNAs [5,16–26].”
miRSystem: An Integrated System for Characterizing Enriched Functions and Pathways of MicroRNA Targets (2012, neutral): “Seven algorithms predicting miRNA targets, DIANA-microT [13] [14], miRanda [9] [22] [23], mirBridge [15], PicTar [16], PITA [18] , rna22 [17] , and TargetScan [10] [11] [12], and two experimentally validated databases, TarBase [24] and miRecords [25], of miRNA target genes were included.”
MicroRNAs in Common Human Diseases (2012, neutral): “Keywords: MicroRNA; Human diseases; Diagnostics; Therapeutics; Biomarker”
miRBase: integrating microRNA annotation and deep-sequencing data (2010, positive): “In its place, we will develop an aggregation service that integrates microRNA target predictions from all the popular target prediction sites [for example, TargetScan (19), PicTar (20), microCosm, DIANA-microT (21), microrna.”
Tools for Sequence-Based miRNA Target Prediction: What to Choose? (2016, positive): “The overall miTG score is calculated as the weighted sum of the scores of all identified MREs on the 3′ UTR [96].”
Supplemental Information Supplemental Data (2014, neutral): “…databases were used: MIRDB release 14 (Wang, 2008; Wang and El Naqa, 2008), Targetscan 5.1 (Friedman et al, 2009), MICROCOSM v5 (Griffiths-Jones et al, 2008), DIANA 3.0 (Maragkakis et al, 2009a; Maragkakis et al, 2009b), RNA22 (august 2007) (Miranda et al, 2006) and PITA v6 (Kertesz et al, 2007).”
MicroRNAs and complex diseases: from experimental results to computational models (2019, positive): “In the tools of RNAhybrid [76] and DIANA micro-T [77], thermal stability plays the former role, while in miRanda [74], PicTar [78] and MicroInspector [79], it acts as a secondary filtering instead.”