Skip to main content

Table 3 Five-fold cross-validation results of the models trained with various features for classifying between 101 carbonylated and 504 non-carbonylated arginine 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

0.614

0.603

0.605

0.163

AAC

0.653

0.683

0.678

0.259

AAPC

0.663

0.687

0.683

0.270

PWM

0.713

0.718

0.717

0.336

PSSM

0.624

0.685

0.674

0.239

ASA

0.594

0.599

0.598

0.145

AAindex

0.693

0.726

0.721

0.329

J48 DT

AA

0.554

0.603

0.595

0.119

AAC

0.594

0.683

0.668

0.214

AAPC

0.614

0.687

0.674

0.233

PWM

0.614

0.675

0.664

0.222

PSSM

0.554

0.665

0.646

0.169

ASA

0.535

0.599

0.588

0.101

AAindex

0.646

0.690

0.683

0.259

RF

AA

0.614

0.605

0.607

0.165

AAC

0.634

0.683

0.674

0.244

AAPC

0.653

0.683

0.678

0.259

PWM

0.713

0.716

0.716

0.334

PSSM

0.624

0.685

0.674

0.239

ASA

0.594

0.599

0.598

0.145

AAindex

0.693

0.724

0.719

0.327

  1. The numbers marked with italicized font are the highest values in four measurements