Table 3 AUPR results for interaction prediction under validation
From: SSELM-neg: spherical search-based extreme learning machine for drug–target interaction prediction
Method | Datasets | |||
|---|---|---|---|---|
E | GPCR | IC | NR | |
Bigram-PSSM | 0.546 | 0.282 | 0.390 | 0.411 |
iDTI-ESBoost | 0.680 | 0.500 | 0.480 | 0.701 |
NRLMF | 0.892 | 0.749 | 0.906 | 0.701 |
BLM-NII | 0.869 | 0.709 | 0.909 | 0.701 |
SPLCMF | 0.881 | 0.754 | 0.938 | 0.533 |
WNN-GIP [79] | 0.706 | 0.520 | 0.717 | 0.589 |
NetLapRLS | 0.786 | 0.617 | 0.820 | 0.463 |
SELF-BLM | 0.639 | 0.599 | 0.744 | 0.457 |
SSELM-neg | 0.982 | 0.991 | 0.982 | 0.946 |