a catalog of biological databases
|Full name:||Database on lncRNA-disease associations|
|Description:||The LncRNADisease database is not only a resource that curated the experimentally supported lncRNA-disease association data but also a platform that integrated tool(s) for predicting novel lncRNA-disease associatons.|
|Address:||38 Xueyuan Road,Beijing,100190,China|
|Contact name (PI/Team):||Qinghua Cui|
|Contact email (PI/Helpdesk):||email@example.com|
Annotation and curation of the causality information in LncRNADisease. [PMID: 31942978]
Disease causative non-coding RNAs (ncRNAs) are of great importance in understanding a disease, for they directly contribute to the development or progress of a disease. Identifying the causative ncRNAs can provide vital implications for biomedical researches. In this work, we updated the long non-coding RNA disease database (LncRNADisease) with long non-coding RNA (lncRNA) causality information with manual annotations of the causal associations between lncRNAs/circular RNAs (circRNAs) and diseases by reviewing related publications. Of the total 11 568 experimental associations, 2297 out of 10 564 lncRNA-disease associations and 198 out of 1004 circRNA-disease associations were identified to be causal, whereas 635 lncRNAs and 126 circRNAs were identified to be causative for the development or progress of at least one disease. The updated information and functions of the database can offer great help to future researches involving lncRNA/circRNA-disease relationship. The latest LncRNADisease database is available at http://www.rnanut.net/lncrnadisease.
LncRNADisease 2.0: an updated database of long non-coding RNA-associated diseases. [PMID: 30285109]
Mounting evidence suggested that dysfunction of long non-coding RNAs (lncRNAs) is involved in a wide variety of diseases. A knowledgebase with systematic collection and curation of lncRNA-disease associations is critically important for further examining their underlying molecular mechanisms. In 2013, we presented the first release of LncRNADisease, representing a database for collection of experimental supported lncRNA-disease associations. Here, we describe an update of the database. The new developments in LncRNADisease 2.0 include (i) an over 40-fold lncRNA-disease association enhancement compared with the previous version; (ii) providing the transcriptional regulatory relationships among lncRNA, mRNA and miRNA; (iii) providing a confidence score for each lncRNA-disease association; (iv) integrating experimentally supported circular RNA disease associations. LncRNADisease 2.0 documents more than 200 000 lncRNA-disease associations. We expect that this database will continue to serve as a valuable source for potential clinical application related to lncRNAs. LncRNADisease 2.0 is freely available at http://www.rnanut.net/lncrnadisease/.
LncRNADisease: a database for long-non-coding RNA-associated diseases. [PMID: 23175614]
In this article, we describe a long-non-coding RNA (lncRNA) and disease association database (LncRNADisease), which is publicly accessible at http://cmbi.bjmu.edu.cn/lncrnadisease. In recent years, a large number of lncRNAs have been identified and increasing evidence shows that lncRNAs play critical roles in various biological processes. Therefore, the dysfunctions of lncRNAs are associated with a wide range of diseases. It thus becomes important to understand lncRNAs' roles in diseases and to identify candidate lncRNAs for disease diagnosis, treatment and prognosis. For this purpose, a high-quality lncRNA-disease association database would be extremely beneficial. Here, we describe the LncRNADisease database that collected and curated approximately 480 entries of experimentally supported lncRNA-disease associations, including 166 diseases. LncRNADisease also curated 478 entries of lncRNA interacting partners at various molecular levels, including protein, RNA, miRNA and DNA. Moreover, we annotated lncRNA-disease associations with genomic information, sequences, references and species. We normalized the disease name and the type of lncRNA dysfunction and provided a detailed description for each entry. Finally, we developed a bioinformatic method to predict novel lncRNA-disease associations and integrated the method and the predicted associated diseases of 1564 human lncRNAs into the database.