An integrative approach to CTL epitope prediction: A combined algorithm integrating MHC class I binding, TAP transport efficiency, and proteasomal cleavage predictions

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A comprehensive review and performance evaluation of bioinformatics tools for HLA class I peptide-binding prediction (2020, methodology): “However, as binding to these HLA allotypes are very specific and there would only exist a few allotype-specific HLA binders originating from one source protein, the proportion of misclassified peptides is likely very small [62, 63].”
The Immune Epitope Database and Analysis Resource in Epitope Discovery and Synthetic Vaccine Design (2017, methodology): “Additional processing predictors are the neural network based tools, NetChop (30, 31), NetCTL (32), and NetCTLpan (33).”
Immune epitope database analysis resource (IEDB-AR) (2008, methodology): “In the new release, alternative approaches were implemented: NetChop (9) uses novel sequence encoding methods to predict proteasomal cleavage, and NetCTL (10,11) combines these with predictions of MHC binding and TAP transport.”
An overview of bioinformatics tools for epitope prediction: Implications on vaccine development (2015, methodology): “based on cascade SVM, using sequence and properties of the amino acids [44,45].”
Large-scale validation of methods for cytotoxic T-lymphocyte epitope prediction (2007, methodology): “We used the BIMAS HLA Peptide Binding Prediction method, since we have previously found this method to be superior [10].”