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Table 4 Performance comparison among the AMPs prediction methods reported in [12] with our proposed approach for the APD3 dataset

From: Optimal selection of molecular descriptors for antimicrobial peptides classification: an evolutionary feature weighting approach

Tool Task Sens(%) Spec(%) Prec(%) Bal Acc(%)
MOEA-FW(SVM-L) Antimicrobial 89.24 82.87 5 1 . 9 8 8 6 . 0 5
CAMPR3(RF)   9 4 . 8 0 a 72.65 40.30 82.49
CAMPR3(SVM)   90.60 72.10 39.25 81.11
ADAM   91.07 68.88 35.09 76.49
MLAMP   75.59 82.27 41.78 72.94
DBAASP   62.81 92.87 38.28 57.49
AMPA   39.17 8 4 . 7 9 39.09 66.80
MOEA-FW(SVM-L) Antibacterial 8 1 . 9 4 9 1 . 5 5 6 5 . 9 2 8 6 . 7 5
AntiBP2   66.59 26.00 15.25 46.30
MOEA-FW(SVM-L) Bacteriocin 9 3 . 1 0 92.95 71.05 93.03
BAGEL3   86.36 1 0 0 . 0 1 0 0 . 0 9 3 . 1 8
BACTIBASE   38.36 1 0 0 . 0 1 0 0 . 0 69.48
  1. aBold font indicates the best value per measure