Table 4 Performance comparison of deep learning architectures
From: CapsNet-SSP: multilane capsule network for predicting human saliva-secretory proteins
Architectures | Accuracy | Sensitivity | Specificity | Precision | F-score | MCC | AUC |
|---|---|---|---|---|---|---|---|
DeepSig | 0.792 (0.011) | 0.745 (0.030) | 0.838 (0.009) | 0.820 (0.016) | 0.781 (7.8e-04) | 0.586 (0.011) | 0.867 (5.8e-07) |
DanQ | 0.802 (1.4e-05) | 0.745 1.8e-05) | 0.859 (3.5e-05) | 0.839 (3.3e-05) | 0.789 (2.2e-05) | 0.608 (1.8e-05) | 0.886 (6.3e-06) |
DeepLoc | 0.843 (0.013) | 0.755 (0.029) | 0.929 (0.037) | 0.914 (0.038) | 0.827 (0.016) | 0.695 (0.013) | 0.891 (0.015) |
CapsNet-SSP | 0.888 (N/A) | 0.847 (N/A) | 0.929 (N/A) | 0.922 (N/A) | 0.884 (N/A) | 0.779 (N/A) | 0.948 (N/A) |