School of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin, Heilongjiang, China.
State Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou, China.
RNA Biol. 2021 Dec;18(12):2354-2362. doi: 10.1080/15476286.2021.1913302. Epub 2021 Apr 27.
N6-methyladenosine (mA) modification is an important regulatory factor affecting diseases, including multiple cancers and it is a developing direction for targeted disease therapy. Here, we present the M6ADD (mA-diseases database) database, a public data resource containing manually curated data on potential mA-disease associations for which some experimental evidence is available; the related high-throughput sequencing data are also provided and analysed by using different computational methods. To give researchers a tool to query the m6A modification data, the M6ADD was designed as a web-based comprehensive resource focusing on the collection, storage and online analysis of m6A modifications, aimed at exploring the associations between m6A modification and gene disorders and diseases. The M6ADD includes 222 experimentally confirmed mA-disease associations, involving 59 diseases from a review of more than 2000 published papers. The M6ADD also includes 409,229 mA-disease associations obtained by computational and statistical methods from 30 high-throughput sequencing datasets. In addition, we provide data on 5239 potential mA regulatory proteins related to 24 cancers based on network analysis prediction methods. In addition, we have developed a tool to explore the function of mA-modified genes through the protein-protein interaction networks. The M6ADD can be accessed at http://m6add.edbc.org/.
N6-甲基腺苷(mA)修饰是影响疾病的重要调节因子,包括多种癌症,是靶向疾病治疗的一个发展方向。在这里,我们展示了 M6ADD(mA 疾病数据库)数据库,这是一个公共数据资源,包含了潜在的 mA 疾病关联的人工策论文献,其中一些有实验证据;还提供了相关的高通量测序数据,并通过不同的计算方法进行分析。为了给研究人员提供一个查询 m6A 修饰数据的工具,M6ADD 被设计为一个基于网络的综合资源,专注于 m6A 修饰的收集、存储和在线分析,旨在探索 m6A 修饰与基因紊乱和疾病之间的关联。M6ADD 包括 222 个经实验证实的 mA 疾病关联,涉及 59 种疾病,这些疾病是从对 2000 多篇已发表论文的综述中得出的。M6ADD 还包括通过 30 个高通量测序数据集的计算和统计方法获得的 409229 个 mA 疾病关联。此外,我们还基于网络分析预测方法提供了与 24 种癌症相关的 5239 个潜在 mA 调节蛋白的数据。此外,我们还开发了一种通过蛋白质-蛋白质相互作用网络探索 mA 修饰基因功能的工具。M6ADD 可在 http://m6add.edbc.org/ 访问。