Results on test set of KIBA dataset based on MRBDTA and existing baseline methods
| Method . | CI (SD) . | MSE (SD) . | rm2 (SD) . |
|---|---|---|---|
| KronRLS | 0.782 (0.0009) | 0.411 | 0.342 (0.001) |
| SimBoost | 0.836 (0.001) | 0.222 | 0.629 (0.007) |
| DeepDTA | 0.863 (0.002) | 0.194 | 0.673 (0.009) |
| MT-DTI | 0.882 (0.001) | 0.152 | 0.738 (0.006) |
| WideDTA | 0.875 (0.001) | 0.179 | – |
| DeepCPI | 0.852 (−) | 0.211 | 0.657 (−) |
| DeepCDA | 0.889 (0.002) | 0.176 | 0.682 (0.008) |
| GraphDTA | 0.891 (−) | 0.139 | – |
| DeepGS | 0.860 (−) | 0.193 | 0.684 (−) |
| MATT_DTI | 0.889 (0.001) | 0.150 | 0.756 (0.011) |
| DeepFusionDTA | 0.876 (−) | 0.176 | – |
| MRBDTA | 0.892 (0.002) | 0.146 (0.001) | 0.778 (0.005) |
| Method . | CI (SD) . | MSE (SD) . | rm2 (SD) . |
|---|---|---|---|
| KronRLS | 0.782 (0.0009) | 0.411 | 0.342 (0.001) |
| SimBoost | 0.836 (0.001) | 0.222 | 0.629 (0.007) |
| DeepDTA | 0.863 (0.002) | 0.194 | 0.673 (0.009) |
| MT-DTI | 0.882 (0.001) | 0.152 | 0.738 (0.006) |
| WideDTA | 0.875 (0.001) | 0.179 | – |
| DeepCPI | 0.852 (−) | 0.211 | 0.657 (−) |
| DeepCDA | 0.889 (0.002) | 0.176 | 0.682 (0.008) |
| GraphDTA | 0.891 (−) | 0.139 | – |
| DeepGS | 0.860 (−) | 0.193 | 0.684 (−) |
| MATT_DTI | 0.889 (0.001) | 0.150 | 0.756 (0.011) |
| DeepFusionDTA | 0.876 (−) | 0.176 | – |
| MRBDTA | 0.892 (0.002) | 0.146 (0.001) | 0.778 (0.005) |
The bold values means the best results among MRBDTA and 11 previous state-of-the-art computational models
Results on test set of KIBA dataset based on MRBDTA and existing baseline methods
| Method . | CI (SD) . | MSE (SD) . | rm2 (SD) . |
|---|---|---|---|
| KronRLS | 0.782 (0.0009) | 0.411 | 0.342 (0.001) |
| SimBoost | 0.836 (0.001) | 0.222 | 0.629 (0.007) |
| DeepDTA | 0.863 (0.002) | 0.194 | 0.673 (0.009) |
| MT-DTI | 0.882 (0.001) | 0.152 | 0.738 (0.006) |
| WideDTA | 0.875 (0.001) | 0.179 | – |
| DeepCPI | 0.852 (−) | 0.211 | 0.657 (−) |
| DeepCDA | 0.889 (0.002) | 0.176 | 0.682 (0.008) |
| GraphDTA | 0.891 (−) | 0.139 | – |
| DeepGS | 0.860 (−) | 0.193 | 0.684 (−) |
| MATT_DTI | 0.889 (0.001) | 0.150 | 0.756 (0.011) |
| DeepFusionDTA | 0.876 (−) | 0.176 | – |
| MRBDTA | 0.892 (0.002) | 0.146 (0.001) | 0.778 (0.005) |
| Method . | CI (SD) . | MSE (SD) . | rm2 (SD) . |
|---|---|---|---|
| KronRLS | 0.782 (0.0009) | 0.411 | 0.342 (0.001) |
| SimBoost | 0.836 (0.001) | 0.222 | 0.629 (0.007) |
| DeepDTA | 0.863 (0.002) | 0.194 | 0.673 (0.009) |
| MT-DTI | 0.882 (0.001) | 0.152 | 0.738 (0.006) |
| WideDTA | 0.875 (0.001) | 0.179 | – |
| DeepCPI | 0.852 (−) | 0.211 | 0.657 (−) |
| DeepCDA | 0.889 (0.002) | 0.176 | 0.682 (0.008) |
| GraphDTA | 0.891 (−) | 0.139 | – |
| DeepGS | 0.860 (−) | 0.193 | 0.684 (−) |
| MATT_DTI | 0.889 (0.001) | 0.150 | 0.756 (0.011) |
| DeepFusionDTA | 0.876 (−) | 0.176 | – |
| MRBDTA | 0.892 (0.002) | 0.146 (0.001) | 0.778 (0.005) |
The bold values means the best results among MRBDTA and 11 previous state-of-the-art computational models
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