4.8 Article

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

Journal

NUCLEIC ACIDS RESEARCH
Volume 41, Issue D1, Pages D239-D245

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/nar/gks1246

Keywords

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Funding

  1. Greek General Secretariat for Research and Technology [09 SYN-13-1055, 09 SYN-13-901]
  2. Project 'MIKRORNA'

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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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