Functional genomics networks are widely used to identify unexpected pathway relationships in large genomic datasets. However, it is challenging to compare the signal-to-noise ratios of different networks and to identify the optimal network with which to interpret a particular genetic dataset. We present GeNets, a platform in which users can train a machine-learning model (Quack) to carry out these comparisons and execute, store, and share analyses of genetic and RNA-sequencing datasets.

中文翻译：

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GeNets：用于基于网络的基因组分析的统一Web平台

功能基因组网络被广泛用于识别大型基因组数据集中意想不到的途径关系。但是，比较不同网络的信噪比并确定用于解释特定遗传数据集的最佳网络具有挑战性。我们介绍了GeNets，一个平台，用户可以在其中训练机器学习模型（Quack）来进行这些比较，以及执行，存储和共享遗传和RNA测序数据集的分析。