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Network modeling of kinase inhibitor polypharmacology reveals pathways targeted in chemical screens

Fig 3

General approach for data integration using the SAMNet algorithm.

We used the SAMNet algorithm to model the cellular response to gemcitabine. SAMNet uses as inputs i) kinases that are predicted to be targeted by the eight gemcitabine-synergizing kinase inhibitors discovered, ii) genetic modifiers of gemcitabine efficacy (genetic hits), iii) genes changing in expression upon gemcitabine treatment, and iv) a TF-gene network based on TF motif matches in open chromatin regions in the promoters of the differentially expressed genes. The SAMNet algorithm then connects the input kinases and genetic hits to the differentially expressed genes through the protein-protein and the TF-gene interactomes in a constrained optimization setting. To distinguish networks anchored in kinase target hits from those anchored in genetic hits, we defined two optimization problems (or commodities) that are solved simultaneously. These are depicted as purple and blue.

Fig 3