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Fig. 3 | BMC Bioinformatics

Fig. 3

From: SWnet: a deep learning model for drug response prediction from cancer genomic signatures and compound chemical structures

Fig. 3

Gene weight layer. Gene feature was combined as the sum of normalized gene expression value and a weight adjusted genetic mutation value. Two ways of generating the mutation component were tested. a Single weight layer: a common weight vector \(w'\) was applied to all genetic mutations without considering the heterogeneity of gene-drug relationship. b Multiple weight layers: a weight matrix \(W'\) was applied to account for the heterogeneity of gene-drug relationship so that each drug would have its own weight vector for genetic mutation

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