Table 1.
Overview of the MHC-peptide binding affinity dataset.
Table 2.
Overview of nine MHC class II peptide prediction methods tested with the new dataset.
Figure 1.
Performance of nine MHC class II prediction methods using HLA DRB1*0101 as an example.
Prediction results for eight methods for HLA DRB1*0101 are shown in the ROC curve. The curves were generated by plotting the true positive rate (y-axis) against the false positive rate (x-axis). The AUC values for corresponding ROC curves were shown in parentheses.
Table 3.
Performance of various MHC class II prediction methodsa.
Table 4.
MHC class II structures used to evaluate the performance of different MHC class II epitope prediction methods.
Table 5.
Accuracy of MHC class II prediction methods for identifying epitope core regions.
Figure 2.
The performance of various MHC class II binding prediction approaches to identify CD4+ T cell epitopes.
ROC curves are generated from the predictions made by five MHC class II peptide binding prediction methods on the LCMV CD4+ T cell activation data. The AUC value for each method is shown in parentheses.
Table 6.
Sensitivity and positive predictive value for predicting T cell activation.