LncRNADisease: a database for long-non-coding RNA-associated diseases

• Published in: Nucleic acids research 2013-01, Vol.41 (Database issue), p.D983-D986
• Main Authors: Chen, Geng, Wang, Ziyun, Wang, Dongqing, Qiu, Chengxiang, Liu, Mingxi, Chen, Xing, Zhang, Qipeng, Yan, Guiying, Cui, Qinghua
• Format: Article
• Language: English
• Subjects: Computational Biology - methods; Databases, Nucleic Acid; Disease - genetics; Humans; Internet; Molecular Sequence Annotation; RNA, Long Noncoding - chemistry; RNA, Long Noncoding - genetics; RNA, Long Noncoding - metabolism
• ISSN: 0305-1048; 1362-4962
• DOI: 10.1093/nar/gks1099

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.