TEpredict: predicting T-cell epitopes
SYFPEITHI (This server finds potential epitopes searching for motifs. It predicts binders for MHC class I or MHC class II molecules) http://www.syfpeithi.de/
RankPep (This server is based on the PSSM approach. It predicts binders for MHC class I or MHC class II molecules. It could predict proteasomal processing as well) http://bio.dfci.harvard.edu/RANKPEP/
SVMHC (This programm is based on the SVM (support vector machine) classification. It predicts binders for MHC class I or MHC class II molecules) http://www-bs.informatik.uni-tuebingen.de/SVMHC/
SVRMHC (This server is based on the SVR (support vector regression). It predicts binders for MHC class I molecules) http://svrmhc.umn.edu/SVRMHCdb/
ProPred1 (This server is based on the QM (quantitative matrices) approach. It predicts binders for MHC class I molecules and is able to predict proteasomal/immunoproteasomal processing of antigens) http://www.imtech.res.in/raghava/propred1/
ProPred (This server is based on the QM (quantitative matrices) approach. It predicts binders for MHC class II molecules) http://www.imtech.res.in/raghava/propred/
nHLAPred (This server is based on the QM (quantitative matrices) and ANN (artificial neural network) approach. It predicts binders for MHC class I molecules and is able to predict proteasomal/immunoproteasomal processing of antigens) http://www.imtech.res.in/raghava/nhlapred/neural.html
CTLPred (This server uses SVM or/and ANN approaches. It predicts binders for MHC class I molecules) http://www.imtech.res.in/raghava/ctlpred/
This list will be continued.