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Table 4 Performance comparison among prediction servers for antimicrobial peptides, a motif-based classification method and rough set theory approach

From: Antimicrobial peptide similarity and classification through rough set theory using physicochemical boundaries

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