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DIANA-LncBase: experimentally verified and computationally predicted microRNA targets on long non-coding RNAs

by: Maria D. Paraskevopoulou, Georgios Georgakilas, Nikos Kostoulas, Martin Reczko, Manolis Maragkakis, Theodore M. Dalamagas, Artemis G. Hatzigeorgiou
Nucleic Acids Research, Vol. 41, No. D1. (01 January 2013), pp. D239-D245, doi:10.1093/nar/gks1246  Key: citeulike:11859839

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Abstract

Recently, the attention of the research community has been focused on long non-coding RNAs (lncRNAs) and their physiological/pathological implications. As the number of experiments increase in a rapid rate and transcriptional units are better annotated, databases indexing lncRNA properties and function gradually become essential tools to this process. Aim of DIANA-LncBase (www.microrna.gr/LncBase) is to reinforce researchers’ attempts and unravel microRNA (miRNA)–lncRNA putative functional interactions. This study provides, for the first time, a comprehensive annotation of miRNA targets on lncRNAs. DIANA-LncBase hosts transcriptome-wide experimentally verified and computationally predicted miRNA recognition elements (MREs) on human and mouse lncRNAs. The analysis performed includes an integration of most of the available lncRNA resources, relevant high-throughput HITS-CLIP and PAR-CLIP experimental data as well as state-of-the-art in silico target predictions. The experimentally supported entries available in DIANA-LncBase correspond to >5000 interactions, while the computationally predicted interactions exceed 10 million. DIANA-LncBase hosts detailed information for each miRNA–lncRNA pair, such as external links, graphic plots of transcripts’ genomic location, representation of the binding sites, lncRNA tissue expression as well as MREs conservation and prediction scores.


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