Table 1 Performances on a testing set of a vanilla neural network, kNN, linear models with different chemical features, TTWOPT and DeepCE with its simpler variants trained with different training sets
Training sets | Models | Features | Pearson | r.m.s.e. | GSEA | Positive P@100 | Negative P@100 |
|---|---|---|---|---|---|---|---|
Original | Vanilla neural network | PubChem | 0.1101 | — | — | — | — |
ECFP | 0.0705 | — | — | — | — | ||
Drug-target | 0.1076 | — | — | — | — | ||
LTIP | 0.0770 | — | — | — | — | ||
kNN | PubChem | 0.0844 | — | — | — | — | |
ECFP | 0.1469 | — | — | — | — | ||
Drug-target | 0.1811 | — | — | — | — | ||
LTIP | 0.1231 | — | — | — | — | ||
High-quality | Vanilla neural network | PubChem | 0.3929 | 1.8413 | 0.3853 | 0.2230 | 0.2622 |
ECFP | 0.4105 | 1.8218 | 0.4049 | 0.2353 | 0.2690 | ||
Drug-target | 0.4270 | 1.8002 | 0.4098 | 0.2334 | 0.2788 | ||
LTIP | 0.4259 | 1.7843 | 0.4168 | 0.2361 | 0.2798 | ||
Random | 0.3129 | 1.9152 | 0.3299 | 0.1729 | 0.2284 | ||
kNN | PubChem | 0.3903 | 1.8464 | 0.3877 | 0.2089 | 0.2606 | |
ECFP | 0.3991 | 1.8264 | 0.4041 | 0.2186 | 0.2639 | ||
Drug-target | 0.3907 | 1.8375 | 0.4105 | 0.2182 | 0.2625 | ||
LTIP | 0.3922 | 1.8388 | 0.3959 | 0.2176 | 0.2578 | ||
Linear Regression | PubChem | 0.1762 | 1.9821 | 0.2184 | 0.1220 | 0.1956 | |
ECFP | 0.1770 | 1.9916 | 0.2227 | 0.1232 | 0.1956 | ||
Drug-target | 0.1763 | 1.9768 | 0.2216 | 0.1240 | 0.1957 | ||
LTIP | 0.1764 | 1.9769 | 0.2232 | 0.1230 | 0.1956 | ||
Lasso | PubChem | 0.1761 | 1.9775 | 0.2160 | 0.1203 | 0.1935 | |
ECFP | 0.1770 | 1.9763 | 0.2237 | 0.1198 | 0.1961 | ||
Drug-target | 0.1764 | 1.9764 | 0.2177 | 0.1209 | 0.1935 | ||
LTIP | 0.1764 | 1.9764 | 0.2177 | 0.1213 | 0.1916 | ||
Ridge Regression | PubChem | 0.1762 | 1.9809 | 0.2185 | 0.1220 | 0.1961 | |
ECFP | 0.1770 | 1.9839 | 0.2254 | 0.1236 | 0.1953 | ||
Drug-target | 0.1764 | 1.9764 | 0.2221 | 0.1232 | 0.1956 | ||
LTIP | 0.1764 | 1.9762 | 0.2237 | 0.1215 | 0.1953 | ||
TT-WOPT | N/A | 0.0133 | 1.9695 | 0.0121 | 0.1228 | 0.1342 | |
Deep CE−attn | Neural FP | 0.4418 | 1.7738 | 0.4088 | 0.2435 | 0.2827 | |
Deep CE−drug−gene attn | 0.4620 | 1.7418 | 0.4493 | 0.2667 | 0.3088 | ||
Deep CE−gene−gene attn | 0.4477 | 1.7711 | 0.4244 | 0.2784 | 0.2961 | ||
Deep CE | 0.4907 | 1.6889 | 0.4656 | 0.2885 | 0.3195 | ||
Augmented | Vanilla neural network | PubChem | 0.4204 | 1.8140 | 0.3932 | 0.2282 | 0.2736 |
ECFP | 0.4177 | 1.8102 | 0.4171 | 0.2191 | 0.2783 | ||
Drug-target | 0.4302 | 1.8092 | 0.4263 | 0.2130 | 0.2785 | ||
LTIP | 0.4299 | 1.7819 | 0.4237 | 0.2259 | 0.2810 | ||
kNN | PubChem | 0.3973 | 1.8392 | 0.3927 | 0.2023 | 0.2615 | |
ECFP | 0.4121 | 1.8020 | 0.4204 | 0.2202 | 0.2809 | ||
Drug-target | 0.4023 | 1.8072 | 0.4011 | 0.2232 | 0.2794 | ||
LTIP | 0.4016 | 1.8223 | 0.3924 | 0.2184 | 0.2650 | ||
DeepCE | Neural FP | 0.5014 | 1.6810 | 0.4735 | 0.2940 | 0.3249 |