Table 3

The HLA-DR ligand benchmark.

Allele

N

NetMHCIIpan

TEPITOPE

NN-W-P1

NN-W

NN-xPFR


DRB1*0101

37

0.873

0.883

    0.899

0.882

0.863

DRB1*0301

26

0.882

0.837

0.862

    0.906

0.788

DRB1*0401

209

0.865

    0.876

0.865

0.843

0.848

DRB1*0404

46

    0.817

0.790

0.776

0.772

0.770

DRB1*0405

35

0.848

0.809

    0.892

0.866

0.878

DRB1*0701

36

0.687

0.711

    0.761

0.754

0.757

DRB1*0802

1

0.982

0.914

    0.984

0.979

0.959

DRB1*0901

4

0.865

0.867

0.864

    0.878

DRB1*1101

27

0.873

0.863

    0.894

0.876

0.881

DRB1*1302

21

0.605

    0.761

0.702

0.687

0.681

DRB1*1501

12

0.770

0.729

0.767

0.766

    0.776

DRB3*0101

2

    0.957

0.680

0.730

0.681

DRB4*0101

4

0.471

    0.540

0.492

0.496

DRB5*0101

15

0.840

0.853

    0.877

0.819

0.851


Ave

0.810

0.812

0.804

0.794

Ave*

0.830

0.842

0.824

0.824

Ave**

0.822

0.821

0.844

0.834

0.824


The benchmark data set consists of 475 HLA-DR restricted ligands downloaded from the SYFPEITHI database of MHC ligands covering 14 HLA-DR alleles. The predictive performance was estimated in terms of the AUC as described in the text. Ave is the average per-allele performance over all 14 alleles. Ave* is the average predictive performance over all 475 ligand/HLA-DR pairs. Ave** is the average per allele performance over the 11 alleles covered by the TEPITOPE method. NetMHCIIpan is the HLA-DR pan-specific method described by Nielsen et al. [23]. TEPITOPE refers to the method developed by Sturniolo et al [17]. NN-W-P1 is the NN-based method including data redundancy step-size rescaling and PSSM-P1 amino acid encoding. NN-W is the NN-based method including data redundancy step-size rescaling. NN-xPFR is the NN-W-P1 method excluding peptide flanking residue encoding. For each allele, the best performing NN method is highlighted in bold and the best performing of all methods is underlined.

Nielsen and Lund BMC Bioinformatics 2009 10:296   doi:10.1186/1471-2105-10-296

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