Discovery of Drug Synergies in Gastric Cancer Cells Predicted by Logical Modeling.

ABSTRACT: Discovery of efficient anti-cancer drug combinations is a major challenge, since experimental testing of all possible combinations is clearly impossible. Recent efforts to computationally predict drug combination responses retain this experimental search space, as model definitions typically rely on extensive drug perturbation data. We developed a dynamical model representing a cell fate decision network in the AGS gastric cancer cell line, relying on background knowledge extracted from literature and databases. We defined a set of logical equations recapitulating AGS data observed in cells in their baseline proliferative state. Using the modeling software GINsim, model reduction and simulation compression techniques were applied to cope with the vast state space of large logical models an

SUBMITTER: Flobak A 

PROVIDER: S-EPMC4567168 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature