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

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 critica...

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Detalles Bibliográficos
Autores principales: Chen, Geng, Wang, Ziyun, Wang, Dongqing, Qiu, Chengxiang, Liu, Mingxi, Chen, Xing, Zhang, Qipeng, Yan, Guiying, Cui, Qinghua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3531173/
https://www.ncbi.nlm.nih.gov/pubmed/23175614
http://dx.doi.org/10.1093/nar/gks1099
Descripción
Sumario: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.