Help and FAQ




LncRNAdb is a database providing comprehensive annotations of eukaryotic long non-coding RNAs (lncRNAs).

First published in 2011, lncRNAdb has been active in maintaining its content and has recently been integrated as a member of RNACentral in May 2014.

It is now currently maintained by the Genome Informatics Group headed by A/Prof Marcel Dinger and based at the Kinghorn Cancer Centre, Garvan Institute of Medical Research, Australia.

We welcome all feedback and enquiries. To find our contact information please refer to the contact page. You may also contribute to lncRNAdb by submitting an entry on our contribution page.

Annotated lncRNAs within lncRNAdb include those shown to have, or to be associated with, biological functions in eukaryotes, as well as messenger RNAs that have regulatory roles and lncRNAs of unknown function.
Each entry is manually curated and contains referenced information about the RNA, including sequences, structural information, genomic context, expression, subcellular localization, conservation, functional evidence and other relevant information. Most (~75%) of the catalogued lncRNAs are from mammals, for which more transcriptomic data is available and which have been more intensively studied, but lncRNAs from vertebrates to single-celled eukaryotes have been included.

In addition, lncRNAdb has links to the UCSC Genome Browser for visualization and included expression data from the Illumina Body Atlas data.



Using lncRNAdb


Querying lncRNAdb using the web interface
Enter any search terms (lncRNA name or established alias, function, tissue specificity, species, associated diseases etc.) into the search bar. If you wish to only get results in a particular species, select this from the filter drop-down list.
After clicking the search button, results for the search will be displayed. If desired, information for all results can be downloaded as an XML file.
Alternatively, to browse all records, click the browse icon located at the bottom of the front page and in the header.


How to use the lncRNAdb Blast search
If the user has a sequence of a potential lncRNA, they can utilise the lncRNAdb blast search to compare their sequence to any known, functional lncRNA.

On input of a query sequence by the user, lncRNAdb will return any entries that have significant similarity with the query sequence. 


Using the REST API
To enable easily downloadable content, lncRNAdb includes a REST API for users to download raw data files programmatically.
The API enables access to XML records in three levels, depending on the amount of requested content and the level of detail. In the simplest form, the user can select either the whole record (e.g. or specific content (e.g. for an individual lncRNA. The next level allows access to multiple entries at once. For example, the query finds all the literature records for lncRNAs that are associated with brain cancer. Finally, the users can retrieve specific information for all entries, such as associated interacting components
More information with examples can be found at



Frequently Asked Questions


How does lncRNAdb differ from other databases?
During the recent decade genome wide transcriptome analysis has shown that ~80% of the genome is associated with functions. However only ~1.5% of the genome encodes for proteins while the rest are associated with regulatory elements. Large sequencings consortiums have tried to annotate the genome through computational predictions. The ENCODE project gene annotation list, GENCODE, has predicted that the human genome contains 14,470 lncRNAs whereas only a small proportion of these have been shown to have function.

We have examined thousands of publications in order to find and manually annotate lncRNAs that have been shown to be functional by overexpression or knockdown experiments.
LncRNAdb provides users with a comprehensive list of the functional lncRNAs that have been studied to date.


Why is my lncRNA of interest is not included in lncRNAdb?
LncRNAdb has strict criteria to only include lncRNAs that have been functionally characterised through knockdown or overexpression experiments. This leaves out lncRNAs that have been associated with diseases, but have not had their function characterised.

LncRNAdb is manually curated, and tries to keep up to date by adding more lncRNAs as they are being published.

If you have a lncRNA that you recently have published, you can submit your data through the contribution page. This will make it easier for other researchers to find information about your lncRNA and give it more exposure to the community.
Submitting a contribution will make the process of adding this lncRNA’s data to lncRNAdb faster than simply requesting it to be added.

One of our teammates will manually go through your submission(s) and add the entry to our database if deemed appropriate.


Can I download all the information contained within lncRNAdb?
Yes, the whole database is available to download through the REST API.
Go to to obtain an XML file.


Why is feature “X” missing from an entry page?
If we are unable to find reliable information on a certain feature of a lncRNA, it is not included in that lncRNA’s entry page.

If you believe that information does exist, please contact us and our team will review and update the entry if applicable.


How can I search for all lncRNA from a particular species?
To search lncRNAdb for all entries from a species, leave the search bar blank and set the filter to the species name.


How many lncRNA are in lncRNAdb for a particular species?
When you search for all entries from a particular species, the number of results returned will be the current number of lncRNAdb entries for that species.


How was the word cloud created?
The word cloud was generated by querying PubMed and exacting relevant abstract text in XML format. Abstract text was processed using bash and the R package tm (V0.6) and the word cloud created using the R package wordcloud (V2.5).
Scripts for processing XML format abstracts are available below.



Script Downloads (3.2 KB)

lncRNAdb_wordclouds.R (2.8 KB)