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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