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GeNets: a unified web platform for network-based genomic analyses
Taibo Li1,2,3,4, April Kim1,2, Joseph Rosenbluh2,5
1Department of Surgery, Massachusetts General Hospital, Boston, MA, USA.
Abstract:
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.
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