Table 10 Comparison results of different PPIs prediction methods on S.cerevisiae (core subset)
From: SDNN-PPI: self-attention with deep neural network effect on protein-protein interaction prediction
Methods | ACC(%) | Spec(%) | Sens(%) | Prec(%) | MCC(%) | AUC(%) |
|---|---|---|---|---|---|---|
DeepPPI[34] | 94.43 ± 0.30 | N/A | 92.06 ± 0.36 | 96.65 ± 0.59 | 88.97 ± 0.62 | N/A |
DeepFE-PPI[39] | 94.78 ± 0.61 | N/A | 92.99 ± 0.66 | 96.45 ± 0.87 | 89.62 ± 1.23 | N/A |
LightGBM-PPI[27] | 95.07 | 97.94 | 92.21 | 97.82 | 90.30 | N/A |
Bio2Vec[59] | 93.30 | N/A | 92.70 | 93.55 | 87.49 | 97.20 |
StackPPI[50] | 94.64 | 96.46 | 92.81 | 96.33 | 89.34 | N/A |
GTB-PPI[28] | 95.15 ± 0.25 | N/A | 92.21 ± 0.36 | 97.97 ± 0.60 | 90.45 ± 0.53 | N/A |
AE-LGBM[60] | 95.40 ± 0.20 | 98.70 ± 0.20 | 92.10 ± 0.30 | N/A | 91.00 ± 0.40 | N/A |
GcForest-PPI[41] | 95.44 ± 0.18 | N/A | 92.72 ± 0.44 | 98.05 ± 0.25 | 91.02 ± 0.35 | N/A |
SDNN-PPI | 95.48 ± 0.37 | 97.23 ± 0.66 | 93.80 ± 0.39 | 97.13 ± 0.66 | 91.02 ± 0.74 | 98.63 |