Fig. 1

DeRegNet’s inputs are a biomolecular network (A), such as a signaling or gene regulatory network, and omics measurements (B), such as gene expression data. The latter are mapped onto the nodes of the network acting as node-level measures of deregulation. DeRegNet then extracts the most deregulated subnetwork (C) from the larger regulatory network according to some definition of most deregulated. For a conceptual view of the progression from set enrichment to de novo subnetwork methods we refer to Fig. 2