Table 1 Performance of proposed and baseline models in the task of rediscovering known drug and cell line responses.
From: Drug discovery and mechanism prediction with explainable graph neural networks
Method | Conv type | RMSE (\(\downarrow\)) | PCC (\(\uparrow\)) | \({\textbf{R}}^2\) (\(\uparrow\)) |
|---|---|---|---|---|
tCNN11 | CNN | 0.026 ± 0.000 | 0.920 ± 0.001 | 0.846 ± 0.001 |
GraphDRP25 | GCN | 0.027 ± 0.000 | 0.917 ± 0.001 | 0.840 ± 0.003 |
GAT | 0.042 ± 0.002 | 0.828 ± 0.011 | 0.609 ± 0.034 | |
DeepCDR (exp)26 | GCN | 1.496 ± 0.018 | 0.841 ± 0.003 | 0.532 ± 0.057 |
TGSA (exp)27 | GraphSAGE | 1.072 ± 0.014 | 0.919 ± 0.002 | 0.845 ± 0.004 |
XGDP | GCN | 0.026 ± 0.000 | 0.918 ± 0.001 | 0.843 ± 0.002 |
GAT | 0.026 ± 0.000 | 0.923 ± 0.000 | 0.851 ± 0.001 | |
GAT_E | 0.026 ± 0.000 | 0.922 ± 0.001 | 0.849 ± 0.001 | |
GATv2_E | 0.026 ± 0.000 | 0.921 ± 0.001 | 0.846 ± 0.001 | |
RGCN | 0.026 ± 0.000 | 0.920 ± 0.001 | 0.845 ± 0.001 | |
RGAT | 0.026 ± 0.000 | 0.920 ± 0.001 | 0.846 ± 0.002 |
