. 2017 Nov 8;17(1):559–567. doi: 10.1021/acs.jproteome.7b00675

Table 2. Comparison of the Predictive Performance of NetMHCpan-4.0_BA (the binding affinity prediction score of the NetMHCpan-4.0 method trained on both eluted ligand and peptide binding affinity data) and NetMHCpan-3.0 Models on Quantitative Binding Affinity Data from the IEDB Affinity Data Set^a.

			NetMHCpan-4.0_BA		NetMHCpan-3.0
BoLA-I	no. peps	no. bind	PCC	AUC	PCC	AUC
BoLA-3*00101 (BoLA-AW10)	166	8	0.497	0.816	0.381	0.792
BoLA-1*02301 (BoLA-D18.4)	258	182	0.648	0.832	0.551	0.747
BoLA-6*01301 (BoLA-HD6)	268	219	0.622	0.815	0.482	0.728
BoLA-3*00201 (BoLA-JSP.1)	158	32	0.464	0.703	0.277	0.622
BoLA-T2c	90	84	0.485	0.833	0.455	0.813
BoLA-2*01201 (BoLA-T2a)	167	47	0.691	0.852	0.635	0.812
BoLA-6*04101 (BoLA-T2b)	157	38	0.631	0.835	0.566	0.816
Ave			0.577	0.812	0.478	0.761

Names in parentheses in the first column refer to the historical names for the different alleles. Performance was estimated in terms of Pearson’s correlation coefficient (PCC) and AUC (area under the receiver operator curve). Both of these performance measures take a value of 1 for the perfect and values of 0.0 (PCC)/0.5 (AUC) for a random prediction.

Table 2. Comparison of the Predictive Performance of NetMHCpan-4.0_BA (the binding affinity prediction score of the NetMHCpan-4.0 method trained on both eluted ligand and peptide binding affinity data) and NetMHCpan-3.0 Models on Quantitative Binding Affinity Data from the IEDB Affinity Data Seta.

Table 2. Comparison of the Predictive Performance of NetMHCpan-4.0_BA (the binding affinity prediction score of the NetMHCpan-4.0 method trained on both eluted ligand and peptide binding affinity data) and NetMHCpan-3.0 Models on Quantitative Binding Affinity Data from the IEDB Affinity Data Set^a.