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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