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The LncRNA Connectivity Map: Using LncRNA Signatures to Connect Small Molecules, LncRNAs, and Diseases. 长链非编码 RNA 连通图:利用长链非编码 RNA 特征将小分子、长链非编码 RNA 和疾病联系起来。

The LncRNA Connectivity Map: Using LncRNA Signatures to Connect Small Molecules, LncRNAs, and Diseases.

机构信息

College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.

Department of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing, 163319, China.

出版信息

Sci Rep. 2017 Jul 27;7(1):6655. doi: 10.1038/s41598-017-06897-3.

Abstract

Well characterized the connections among diseases, long non-coding RNAs (lncRNAs) and drugs are important for elucidating the key roles of lncRNAs in biological mechanisms in various biological states. In this study, we constructed a database called LNCmap (LncRNA Connectivity Map), available at http://www.bio-bigdata.com/LNCmap/ , to establish the correlations among diseases, physiological processes, and the action of small molecule therapeutics by attempting to describe all biological states in terms of lncRNA signatures. By reannotating the microarray data from the Connectivity Map database, the LNCmap obtained 237 lncRNA signatures of 5916 instances corresponding to 1262 small molecular drugs. We provided a user-friendly interface for the convenient browsing, retrieval and download of the database, including detailed information and the associations of drugs and corresponding affected lncRNAs. Additionally, we developed two enrichment analysis methods for users to identify candidate drugs for a particular disease by inputting the corresponding lncRNA expression profiles or an associated lncRNA list and then comparing them to the lncRNA signatures in our database. Overall, LNCmap could significantly improve our understanding of the biological roles of lncRNAs and provide a unique resource to reveal the connections among drugs, lncRNAs and diseases.

摘要

深入研究疾病、长链非编码 RNA(lncRNA)和药物之间的关系对于阐明 lncRNA 在各种生物状态下的生物学机制中的关键作用非常重要。在这项研究中,我们构建了一个名为 LNCmap(lncRNA 连接图谱)的数据库,网址为 http://www.bio-bigdata.com/LNCmap/,通过尝试用 lncRNA 特征来描述所有的生物状态,从而建立疾病、生理过程和小分子治疗药物之间的相关性。通过对 Connectivity Map 数据库中的微阵列数据进行重新注释,LNCmap 获得了 237 个 lncRNA 特征,对应 1262 种小分子药物的 5916 个实例。我们提供了一个用户友好的界面,方便用户浏览、检索和下载数据库,包括详细信息以及药物和相应受影响的 lncRNA 的关联。此外,我们还开发了两种富集分析方法,用户可以通过输入相应的 lncRNA 表达谱或相关的 lncRNA 列表,然后将其与我们数据库中的 lncRNA 特征进行比较,来识别特定疾病的候选药物。总之,LNCmap 可以显著提高我们对 lncRNA 生物学作用的理解,并为揭示药物、lncRNA 和疾病之间的关系提供独特的资源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cf9/5532316/f4ff5aedd319/41598_2017_6897_Fig1_HTML.jpg

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