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

被引:753
作者
Chen, Geng [1 ,2 ,3 ]
Wang, Ziyun [2 ]
Wang, Dongqing [2 ]
Qiu, Chengxiang [2 ]
Liu, Mingxi [4 ]
Chen, Xing [4 ]
Zhang, Qipeng [2 ]
Yan, Guiying [4 ]
Cui, Qinghua [1 ,2 ,3 ]
机构
[1] Peking Univ, Sch Basic Med Sci, Dept Biomed Informat, Beijing 100190, Peoples R China
[2] Peking Univ, MOE Key Lab Cardiovasc Sci, Beijing 100190, Peoples R China
[3] Peking Univ, Inst Syst Biomed, Beijing 100190, Peoples R China
[4] Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
基金
中国国家自然科学基金;
关键词
NONCODING RNAS; HUMAN MICRORNA; EXPRESSION; CANCER; ANRIL;
D O I
10.1093/nar/gks1099
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
In this article, we describe a long-non-coding RNA (lncRNA) and disease association database (LncRNADisease), which is publicly accessible at http://cmbi.bjm u.edu.cn/Incrnadisease. 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.
引用
收藏
页码:D983 / D986
页数:4
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