Table 2.
Methods | Residue = S | ||||||
---|---|---|---|---|---|---|---|
AUC (%) | Acc (%) | Sn (%) | Sp (%) | Pre (%) | F1 (%) | MCC | |
TransPhos | 78.67 | 71.53 | 67.16 | 75.89 | 73.59 | 70.23 | 0.432 |
CNN | 74.34 | 68.40 | 61.14 | 75.65 | 71.52 | 65.93 | 0.372 |
LSTM | 77.04 | 70.48 | 65.01 | 75.95 | 72.99 | 68.77 | 0.412 |
RNN | 75.53 | 68.84 | 61.44 | 76.24 | 72.11 | 66.35 | 0.381 |
FCNN | 75.30 | 69.14 | 60.68 | 77.61 | 73.04 | 66.29 | 0.388 |
Methods | Residue = T | ||||||
AUC | Acc | Sn (%) | Sp (%) | Pre (%) | F1 (%) | MCC | |
TransPhos | 67.19 | 61.77 | 47.32 | 76.22 | 66.56 | 55.32 | 0.246 |
CNN | 64.44 | 59.19 | 42.03 | 76.34 | 63.98 | 50.74 | 0.196 |
LSTM | 66.59 | 60.64 | 41.85 | 79.43 | 67.05 | 51.54 | 0.230 |
RNN | 66.03 | 61.21 | 48.57 | 73.84 | 65.00 | 55.60 | 0.232 |
FCNN | 63.94 | 59.63 | 45.30 | 73.96 | 63.50 | 52.88 | 0.201 |
Methods | Residue = Y | ||||||
AUC | Acc | Sn (%) | Sp (%) | Pre (%) | F1 (%) | MCC | |
TransPhos | 60.09 | 55.41 | 38.52 | 72.30 | 58.17 | 46.35 | 0.115 |
CNN | 59.11 | 54.59 | 34.81 | 74.37 | 57.60 | 43.40 | 0.100 |
LSTM | 59.49 | 55.56 | 40.74 | 70.37 | 57.89 | 47.83 | 0.116 |
RNN | 61.71 | 59.48 | 58.96 | 60.00 | 59.58 | 59.27 | 0.190 |
FCNN | 59.30 | 56.44 | 43.26 | 69.63 | 58.75 | 49.83 | 0.134 |
Accuracy (Acc), Sensitivity (Sn), Specificity (Sp), Precision (Pre), F1 Score (F1) and Matthews correlation coefficient (MCC) were calculated to measure the performance of models. Data in bold indicates that the model performs best for that evaluation metric.