Table 1.

Examples of the most commonly used databases and sequence-based algorithms for T-cell epitopes prediction.

Databases	Link	Algorithms used (cited ones)
Immune Epitope Database (IEDB)	http://www.iedb.org/	Stabilized Matrix Method-NetMHC-NetMHCIIpan-NetChop
SYFPEITHI	http://www.syfpeithi.de/	SYFPEITHI
HIV Molecular Immunology Database	http://www.hiv.lanl.gov/
IMGT/HLA Database	http://www.ebi.ac.uk/ipd/imgt/hla/
Sequence-based algorithms	Link	Brief description
SYFPEITHI	http://www.syfpeithi.de/Scripts/MHCServer.dll/EpitopePrediction.htm	Use of anchor residues Score based on frequency in natural ligands
BIMAS	http://www-bimas.cit.nih.gov/molbio/hla_bind/	MHC I epitopes predictor Use of coefficient tables of dissociation halftime
Stabilized Matrix Method	http://tools.immuneepitope.org/main/html/tcell_tools .html	Peters and Sette, 2005  Score system for nonbinders Use of training datasets
NetMHC	http://cbs.dtu.dk/services/NetMHC/	Artificial neural network MHC I epitopes predictor Trained with 57 human HLA
NetMHCIIpan	http://cbs.dtu.dk/services/NetMHCIIpan/	Artificial neural network MHC II epitopes predictor Analyze >500 HLA-DR alleles
PROPRED	http://www.imtech.res.in/raghava/propred/	Use of quantitative matrices derived from the literature MHC II epitopes predictor
NetChop	http://cbs.dtu.dk/services/NetChop/	Artificial neural network Proteasome cleavage predictor Part of NetCTL server
FragPredict	http://www.mpiib-berlin.mpg.de/MAPPP/expertquery.html	Proteasomal cleavage sites and proteolytic fragments predictor Part of MAPPP server