PMC:4331679 / 28420-29460 JSONTXT

{"project":"2_test","denotations":[{"id":"25707537-20221256-14870740","span":{"begin":1029,"end":1030},"obj":"20221256"},{"id":"25707537-22579283-14870741","span":{"begin":1031,"end":1032},"obj":"22579283"},{"id":"25707537-11350724-14870742","span":{"begin":1033,"end":1035},"obj":"11350724"},{"id":"25707537-17616683-14870743","span":{"begin":1036,"end":1038},"obj":"17616683"}],"text":"After inferring N2 from N1, our aim was to infer the drug sensitive network (N3), by fitting modified topology of N2 to the real data of drug treatment. Before predicting rewiring of N2, we plotted the N2 based simulation data with the real dataset of signalling and cell fate of cancer cells after treatment with drugs. The plot is shown in Figure 5. We again used Genetic Algorithm to search for the network rewirings that allow better fitting of simulation to the real data. For each run of simulation, we compared the simulation data with the drug sensitive experimental apoptosis data for ERL-DOX treatments. The best network plot, uncovered using Genetic Algorithm, is shown in Figure 6. The edges of N2 that were most frequently removed were BIM-Casp9 and EGFR-Casp8, deleted 141 and 137 times respectively. The network edges inserted with highest frequencies by the Genetic Algorithm were Casp8-RIP and Casp8-MOMP, inserted 144 and 135 times respectively. These rewiring events have been mentioned in related literature [2,5,17,36]."}