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Table 1 Prediction Results on Benchmark Dataset

From: Integrating peptides' sequence and energy of contact residues information improves prediction of peptide and HLA-I binding with unknown alleles

Allele ANNBM ARB SMM NetMHC Other methods Peptides
A*0101 0.977 0.964 0.98 0.982 0.955 1157
A*0201 0.951 0.934 0.952 0.957 0.922 3089
A*0202 0.891 0.875 0.899 0.9 0.793 1447
A*0203 0.911 0.884 0.916 0.921 0.788 1443
A*0206 0.906 0.872 0.914 0.927 0.735 1437
A*0301 0.932 0.908 0.94 0.937 0.851 2094
A*1101 0.945 0.918 0.948 0.951 0.869 1985
A*2402 0.826 0.718 0.78 0.825 0.77 197
A*2601 0.950 0.907 0.931 0.956 0.736 672
A*2902 0.907 0.755 0.911 0.935 0.597 160
A*3101 0.923 0.909 0.93 0.928 0.829 1869
A*3301 0.915 0.892 0.925 0.915 0.807 1140
A*6801 0.88 0.84 0.885 0.883 0.772 1141
A*6802 0.883 0.865 0.898 0.899 0.643 1434
B*0702 0.966 0.952 0.964 0.965 0.942 1262
B*0801 0.968 0.936 0.943 0.955 0.766 708
B*1501 0.939 0.9 0.952 0.941 0.816 978
B*1801 0.848 0.573 0.853 0.838 0.779 118
B*2705 0.957 0.915 0.94 0.938 0.926 969
B*3501 0.873 0.851 0.889 0.875 0.792 736
B*4002 0.858 0.541 0.842 0.754 0.775 118
B*4402 0.824 0.533 0.74 0.778 0.783 119
B*4403 0.791 0.461 0.77 0.763 0.698 119
B*5101 0.894 0.822 0.868 0.886 0.82 244
B*5301 0.886 0.871 0.882 0.899 0.861 254
B*5401 0.911 0.847 0.921 0.903 0.799 255
B*5701 0.96 0.428 0.871 0.826 0.767 59
B*5801 0.972 0.889 0.964 0.961 0.899 988
AVG 0.909 0.791 0.874 0.901 0.796  
  1. Table 1 summarizes the comparative results between our ANNBM and the methods in the Bjoern Peters work on the benchmark. We use the AUC (Area Under roc Curve) of 5-folds cross validation as the prediction evaluation criterion. In the table, the first column is the allele name, including 14 HLA-A class molecules and 14 HLA-B class molecules. The columns from 2 to 5 are the AUC value of 5-folds cross validation from the ANNBM、 ARB、 SMM and NetMHC respectively. In addition, ANNBM is also compared to other 16 online prediction methods including various outstanding classifiers like SVM (arbmatrix, bimas, hlaligand, hla_a2_smm, libscore, mappp, mhcpathway, mhcpred, multipred, netmhc, pepdist, predbalbc, predep, rankpep, svmhc and syfpeithi) and the best prediction value among them is listed in the column 6. The last column is the number of peptides binding to the corresponding the HLA molecule.