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Prediction of cancer cell sensitivity to natural products based on genomic and chemical properties

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Academic year: 2017

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Table 1 Natural products and the corresponding cancer cell line-natural product interaction data used in the training set, test set and case studies analyses.
Figure 1 Natural products sensitivity prediction workflow. This data flow diagram demonstrates the simulation workflow for creation and optimization of natural products sensitivity prediction model
Figure 2 Comparison between the case K = 2 and K = 3. Bar chart showing in the case K = 3 (blue) we obtained a higher AUC than in the case K = 2 when features number is set as 50
Figure 3 Comparison among different top N significantly differential features. AUCs plotted against different top N features in the case K = 3 are varied
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