Databases for lncRNAs: A comparative evaluation of emerging tools

Sabrina Fritah, Simone P. Niclou, Francisco Azuaje*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

88 Citations (Scopus)


The vast majority of the human transcriptome does not code for proteins. Advances in transcriptome arrays and deep sequencing are giving rise to a fast accumulation of large data sets, particularly of long noncoding RNAs (lncRNAs). Although it is clear that individual lncRNAs may play important and diverse biological roles, there is a large gap between the number of existing lncRNAs and their known relation to molecular/cellular function. This and related information have recently been gathered in several databases dedicated to lncRNA research. Here, we review the content of general and more specialized databases on lncRNAs. We evaluate these resources in terms of the quality of annotations, the reporting of validated or predicted molecular associations, and their integration with other resources and computational analysis tools. We illustrate our findings using known and novel cancer-related lncRNAs. Finally, we discuss limitations and highlight potential future directions for these databases to help delineating functions associated with lncRNAs.

Original languageEnglish
Pages (from-to)1655-1665
Number of pages11
Issue number11
Publication statusPublished - 1 Nov 2014


  • Databases
  • LncRNAs
  • Noncoding RNAs


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