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Table 2 Five-fold cross-validation results of the models trained with various features for classifying between 206 carbonylated and 1166 non-carbonylated lysine 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 0.680 0.643 0.649 0.235
AAC 0.728 0.686 0.692 0.305
AAPC 0.699 0.696 0.697 0.294
PWM 0.748 0.715 0.720 0.346
PSSM 0.704 0.686 0.689 0.288
ASA 0.592 0.571 0.574 0.117
AAindex 0.709 0.720 0.719 0.323
J48 DT AA 0.534 0.557 0.554 0.066
AAC 0.655 0.678 0.674 0.246
AAPC 0.670 0.683 0.681 0.261
PWM 0.689 0.674 0.676 0.267
PSSM 0.621 0.660 0.655 0.207
ASA 0.515 0.563 0.555 0.055
AAindex 0.660 0.682 0.679 0.253
RF AA 0.660 0.635 0.638 0.214
AAC 0.704 0.686 0.689 0.288
AAPC 0.709 0.703 0.704 0.307
PWM 0.718 0.707 0.708 0.317
PSSM 0.699 0.686 0.688 0.285
ASA 0.583 0.583 0.583 0.119
AAindex 0.709 0.717 0.716 0.319
  1. The numbers marked with italicized font are the highest values in four measurements