Evaluation of MHC class I peptide binding prediction servers: Applications for vaccine research

Non-linear predictors outperform matrix-based predictors. Most predictors can be improved by non-linear transformations of their raw prediction scores. The best predictors of peptide binding are also best in prediction of T-cell epitopes. We propose a new standard for MHC-I binding prediction - a common scale for normalization of prediction scores, applicable to both experimental and predicted data. The results of this study provide assistance to researchers in selection of most adequate prediction tools and selection criteria that suit the needs of their projects.