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Discrete dynamical modeling shows promise in prioritizing drug combinations for screening efforts by reducing the experimental workload inherent to the vast numbers of possible drug combinations. We have investigated approaches to predict combination responses across different cancer cell lines using logic models generated from one generic prior-knowledge network representing 144 nodes covering major cancer signaling pathways. Cell-line specific models were configured to agree with baselinedoi:10.3389/fphys.2020.00862 pmid:32848834 pmcid:PMC7399174 fatcat:hwcvvtwusfbk7oxxd7btmevlpu