Table 4.
Performance comparison among prediction servers for antimicrobial peptides, a motif-based classification method and rough set theory approach
| Method | Sensitivity (%) | Specificity (%) | MCC |
|---|---|---|---|
| CAMP SVM | 95.8 | 39.8 | 0.43 |
| CAMP RF | 97.1 | 33.5 | 0.40 |
| CAMP ANN | 89.1 | 70.9 | 0.61 |
| CAMP DA | 94.1 | 49.5 | 0.49 |
| iAMP-2 L | 97.7 | 92.0 | 0.90 |
| EFC-FCBF | 92.0 | 90.0 | 0.73 |
| EFC + 307-FCBF (307 AAindex1 features) |
92.4 | 96.1 | 0.86 |
| CLN-MLEM2 (74 AAindex1 features) |
88.0 | 95.4 | 0.85 |