Institute for Systems Analysis and Computer Science "Antonio Ruberti", National Research Council, Via dei Taurini 19, Rome, 00185, Italy.
Department of Biology and Biotechnology "Charles Darwin", "Sapienza" University of Rome, Via dei Sardi 70, Rome, 00185, Italy.
BMC Bioinformatics. 2019 Nov 4;20(1):545. doi: 10.1186/s12859-019-3105-x.
miRNAs regulate the expression of several genes with one miRNA able to target multiple genes and with one gene able to be simultaneously targeted by more than one miRNA. Therefore, it has become indispensable to shorten the long list of miRNA-target interactions to put in the spotlight in order to gain insight into understanding the regulatory mechanism orchestrated by miRNAs in various cellular processes. A reasonable solution is certainly to prioritize miRNA-target interactions to maximize the effectiveness of the downstream analysis.
We propose a new and easy-to-use web tool MIENTURNET (MicroRNA ENrichment TURned NETwork) that receives in input a list of miRNAs or mRNAs and tackles the problem of prioritizing miRNA-target interactions by performing a statistical analysis followed by a fully featured network-based visualization and analysis. The statistics is used to assess the significance of an over-representation of miRNA-target interactions and then MIENTURNET filters based on the statistical significance associated with each miRNA-target interaction. In addition, the holistic approach of the network theory is used to infer possible evidences of miRNA regulation by capturing emergent properties of the miRNA-target regulatory network that would be not evident through a pairwise analysis of the individual components.
MIENTURNET offers the possibility to consistently perform both statistical and network-based analyses by using only a single tool leading to a more effective prioritization of the miRNA-target interactions. This has the potential to avoid researchers without computational and informatics skills to navigate multiple websites and thus to independently investigate miRNA activity in every cellular process of interest in an easy and at the same time exhaustive way thanks to the intuitive web interface. The web application along with a well-documented and comprehensive user guide are freely available at http://userver.bio.uniroma1.it/apps/mienturnet/ without any login requirement.
miRNAs 调节多个基因的表达，一个 miRNA 可以靶向多个基因，一个基因也可以同时被多个 miRNA 靶向。因此，为了深入了解 miRNA 在各种细胞过程中调控机制，将 miRNA 靶基因相互作用的长列表缩短并突出重点已经变得不可或缺。一个合理的解决方案当然是优先考虑 miRNA 靶基因相互作用，以最大限度地提高下游分析的有效性。
我们提出了一个新的、易于使用的网络工具 MIENTURNET（MicroRNA ENrichment TURned NETwork），它接收 miRNA 或 mRNA 的列表作为输入，并通过执行统计分析，然后进行全面的基于网络的可视化和分析来解决优先考虑 miRNA 靶基因相互作用的问题。该统计用于评估 miRNA 靶基因相互作用过度表达的显著性，然后 MIENTURNET 根据与每个 miRNA 靶基因相互作用相关的统计显著性进行过滤。此外，网络理论的整体方法用于通过捕获 miRNA 靶调控网络的新兴特性来推断 miRNA 调控的可能证据，这些证据通过对单个组件的成对分析是不明显的。
MIENTURNET 提供了仅使用单个工具同时进行统计和基于网络的分析的可能性，从而更有效地优先考虑 miRNA 靶基因相互作用。这有可能避免没有计算和信息学技能的研究人员浏览多个网站，并通过直观的网络界面以简单而全面的方式独立研究每个感兴趣的细胞过程中的 miRNA 活性。该网络应用程序以及详细的用户指南可在 http://userver.bio.uniroma1.it/apps/mienturnet/ 上免费获得，无需登录。
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