The misregulation of microRNA (miRNA) has been shown to cause diseases. Recently, we have proposed a computational method based on a random walk framework on a miRNA-target gene network to predict disease-associated miRNAs. The prediction performance of our method is better than that of some existing state-of-the-art network- and machine learning-based methods since it exploits the mutual regulation between miRNAs and their target genes in the miRNA-target gene interaction networks. To facilitate the use of this method, we have developed a Cytoscape app, named RWRMTN, to predict disease-associated miRNAs. RWRMTN can work on any miRNA-target gene network. Highly ranked miRNAs are supported with evidence from the literature. They then can also be visualized based on the rankings and in relationships with the query disease and their target genes. In addition, automation functions are also integrated, which allow RWRMTN to be used in workflows from external environments. We demonstrate the ability of RWRMTN in predicting breast and lung cancer-associated miRNAs via workflows in Cytoscape and other environments. Considering a few computational methods have been developed as software tools for convenient uses, RWRMTN is among the first GUI-based tools for the prediction of disease-associated miRNAs which can be used in workflows in different environments.

中文翻译：

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RWRMTN：一种基于 microRNA 靶基因网络预测疾病相关 microRNA 的工具。


microRNA (miRNA) 的失调已被证明会导致疾病。最近，我们提出了一种基于 miRNA 靶基因网络上的随机游走框架的计算方法来预测与疾病相关的 miRNA。我们的方法的预测性能优于一些现有的最先进的基于网络和机器学习的方法，因为它利用了 miRNA-靶基因相互作用网络中 miRNA 与其靶基因之间的相互调节。为了方便该方法的使用，我们开发了一款名为 RWRMTN 的 Cytoscape 应用程序来预测与疾病相关的 miRNA。 RWRMTN 可以在任何 miRNA 目标基因网络上工作。排名靠前的 miRNA 得到了文献证据的支持。然后，还可以根据排名以及与查询疾病及其目标基因的关系将它们可视化。此外，还集成了自动化功能，使得RWRMTN可以在外部环境的工作流程中使用。我们通过 Cytoscape 和其他环境中的工作流程展示了 RWRMTN 预测乳腺癌和肺癌相关 miRNA 的能力。考虑到已经开发了一些计算方法作为方便使用的软件工具，RWRMTN 是第一个基于 GUI 的预测疾病相关 miRNA 的工具之一，可以在不同环境的工作流程中使用。