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Fig. 1 | BioData Mining

Fig. 1

From: Interpreting drug synergy in breast cancer with deep learning using target-protein inhibition profiles

Fig. 1

Input features of the drug-synergy prediction model. A group of graph convolutional neural network models generated 13 scores, representing inhibitory activities against 13 protein targets (the target-protein inhibition profile). To predict synergy between two drugs, the target-protein inhibition profile of each drug was concatenated, resulting in 13 × 2 = 26 features. Each feature has a value between 0 and 1. Mutation profiles of seven genes of each cell line retrieved from the Cell Model Passports and DepMap databases were also concatenated, where 0, 1, and 2 represent no mutation, loss-of-function mutation, and gain-of-function mutation, respectively

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