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Table 4 Five-fold cross-validation results of the models trained with various features for classifying between 96 carbonylated and 488 non-carbonylated threonine residues

From: Investigation and identification of protein carbonylation sites based on position-specific amino acid composition and physicochemical features

Classifier Training features Sensitivity Specificity Accuracy MCC
SVM AA 0.625 0.615 0.616 0.180
AAC 0.667 0.656 0.658 0.244
AAPC 0.646 0.660 0.658 0.232
PWM 0.688 0.672 0.675 0.274
PSSM 0.656 0.656 0.656 0.236
ASA 0.573 0.590 0.587 0.122
AAindex 0.667 0.654 0.656 0.242
J48 DT AA 0.604 0.594 0.596 0.148
AAC 0.635 0.635 0.635 0.204
AAPC 0.635 0.641 0.640 0.209
PWM 0.625 0.637 0.635 0.198
PSSM 0.604 0.598 0.599 0.151
ASA 0.573 0.590 0.587 0.122
AAindex 0.646 0.641 0.642 0.217
RF AA 0.625 0.617 0.618 0.181
AAC 0.656 0.652 0.652 0.233
AAPC 0.646 0.652 0.651 0.225
PWM 0.677 0.668 0.670 0.262
PSSM 0.656 0.656 0.656 0.236
ASA 0.583 0.594 0.592 0.133
AAindex 0.656 0.676 0.673 0.254
  1. The numbers makred with italicized font are the highest values in four measurements