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Table 3 Comparison of HLA-DR prediction results on the dataset proposed by the authors of RTA

From: Learning a peptide-protein binding affinity predictor with kernel ridge regression

 

PCC

RMSE (kcal/mol)

 

MHC β chain

KRR+GS

RTA

KRR+GS

RTA

# of examples

DRB1*0101

0.632

0.530

1.20

1.43

5648

DRB1*0301

0.538

0.425

1.16

1.46

837

DRB1*0401

0.430

0.340

1.44

1.72

1014

DRB1*0404

0.491

0.487

1.25

1.38

617

DRB1*0405

0.530

0.442

1.09

1.35

642

DRB1*0701

0.645

0.484

1.24

1.62

833

DRB1*0802

0.469

0.412

1.19

1.34

557

DRB1*0901

0.303

0.369

1.55

1.68

551

DRB1*1101

0.550

0.450

1.17

1.45

812

DRB1*1302

0.468

0.464

1.51

1.64

636

DRB1*1501

0.502

0.438

1.41

1.53

879

DRB3*0101

0.380

0.425

1.03

1.13

483

DRB4*0101

0.613

0.522

1.10

1.33

664

DRB5*0101

0.541

0.434

1.20

1.57

835

H2*IA b

0.603

0.556

1.00

1.15

526

H2*IAd

0.325

0.563

1.44

1.53

306

Average:

0.501

0.459

1.25

1.46

 
  1. Best results for each metric are highlighted in bold. The PCC results show that the proposed method (KRR+GS) outperforms the RTA method with a p-value of 0.0308. The RMSE results show that KRR+GS outperforms the RTA method on all 16 allotypes with a p-value of 0.0005.
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BMC Bioinformatics

ISSN: 1471-2105

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