Table 3.
Scenario | Method | MSE | CI | |
---|---|---|---|---|
Cold drug | GraphDTA | 0.920(0.029) | 0.678(0.036) | 0.160(0.019) |
GEFA | 0.847(0.012) | 0.709(0.028) | 0.182(0.015) | |
FusionDTA | 0.581(0.094) | 0.737(0.012) | 0.187(0.034) | |
MgraphDTA | 0.563(0.065) | 0.729(0.022) | 0.192(0.021) | |
NHGNN(Ours) | 0.554(0.091) | 0.752(0.017) | 0.207(0.030) | |
Cold target | GraphDTA | 0.510(0.086) | 0.729(0.012) | 0.154(0.014) |
GEFA | 0.433(0.022) | 0.759(0.009) | 0.289(0.016) | |
FusionDTA | 0.364(0.021) | 0.826(0.011) | 0.435(0.023) | |
MgraphDTA | 0.359(0.023) | 0.813(0.008) | 0.425(0.028) | |
NHGNN(Ours) | 0.344(0.029) | 0.855(0.016) | 0.479(0.021) | |
All cold | GraphDTA | 0.968(0.096) | 0.579(0.017) | 0.026(0.016) |
GEFA | 0.944(0.092) | 0.610(0.029) | 0.032(0.022) | |
FusionDTA | 0.876(0.091) | 0.645(0.043) | 0.072(0.048) | |
MgraphDTA | 0.874(0.090) | 0.636(0.021) | 0.071(0.041) | |
NHGNN(Ours) | 0.857(0.096) | 0.665(0.038) | 0.087(0.051) |
Bold corresponds to the best performance for each metric, and underline indicates the second best.