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miRNet 2.0:基于网络的 miRNA 功能分析和系统生物学的可视化分析。

miRNet 2.0: network-based visual analytics for miRNA functional analysis and systems biology.

机构信息

Department of Human Genetics, McGill University, Montreal, Quebec, Canada.

Institute of Parasitology, McGill University, Montreal, Quebec, Canada.

出版信息

Nucleic Acids Res. 2020 Jul 2;48(W1):W244-W251. doi: 10.1093/nar/gkaa467.

DOI:10.1093/nar/gkaa467
PMID:32484539
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7319552/
Abstract

miRNet is an easy-to-use, web-based platform designed to help elucidate microRNA (miRNA) functions by integrating users' data with existing knowledge via network-based visual analytics. Since its first release in 2016, miRNet has been accessed by >20 000 researchers worldwide, with ∼100 users on a daily basis. While version 1.0 was focused primarily on miRNA-target gene interactions, it has become clear that in order to obtain a global view of miRNA functions, it is necessary to bring other important players into the context during analysis. Driven by this concept, in miRNet version 2.0, we have (i) added support for transcription factors (TFs) and single nucleotide polymorphisms (SNPs) that affect miRNAs, miRNA-binding sites or target genes, whilst also greatly increased (>5-fold) the underlying knowledgebases of miRNAs, ncRNAs and disease associations; (ii) implemented new functions to allow creation and visual exploration of multipartite networks, with enhanced support for in situ functional analysis and (iii) revamped the web interface, optimized the workflow, and introduced microservices and web application programming interface (API) to sustain high-performance, real-time data analysis. The underlying R package is also released in tandem with version 2.0 to allow more flexible data analysis for R programmers. The miRNet 2.0 website is freely available at https://www.mirnet.ca.

摘要

miRNet 是一个易于使用的基于网络的平台,旨在通过基于网络的可视化分析将用户数据与现有知识集成在一起,帮助阐明 microRNA(miRNA)的功能。自 2016 年首次发布以来,miRNet 已被全球超过 20,000 名研究人员访问,每天约有 100 名用户。虽然版本 1.0 主要关注 miRNA-靶基因相互作用,但很明显,为了获得 miRNA 功能的全局视图,有必要在分析过程中将其他重要参与者纳入其中。受此概念的驱动,在 miRNet 版本 2.0 中,我们(i)添加了对转录因子(TFs)和影响 miRNA、miRNA 结合位点或靶基因的单核苷酸多态性(SNPs)的支持,同时还大大增加了 miRNA、ncRNA 和疾病关联的知识库 (>5 倍);(ii)实现了新的功能,允许创建和可视化探索多部分网络,并增强了原位功能分析的支持;(iii)重新设计了网络界面,优化了工作流程,并引入了微服务和 Web 应用程序编程接口(API),以维持高性能、实时数据分析。同时,与版本 2.0 一起发布的还有底层 R 包,允许 R 程序员进行更灵活的数据分析。miRNet 2.0 网站可在 https://www.mirnet.ca 上免费获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0ee/7319552/0baa7c39d052/gkaa467fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0ee/7319552/c1594610887b/gkaa467fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0ee/7319552/0baa7c39d052/gkaa467fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0ee/7319552/c1594610887b/gkaa467fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0ee/7319552/0baa7c39d052/gkaa467fig2.jpg

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