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Figure courtesy of A. J. Reits

NetCTL 1.2 Server

NetCTL 1.2 server predicts CTL epitopes in protein sequences. The current version 1.2 is an update to the version 1.0. The version 1.2 expands the MHC class I binding predicition to 12 MHC supertypes including the supertypes A26 and B39. The accuracy of the MHC class I peptide binding affinity is significantly improved compared to the earlier version. Also the prediction of proteasonal cleavage has been improved and is now identical to the predictions obtained by the NetChop-3.0 server. The updated version has been trained on a set of 886 known MHC class I ligands.

NOTE. On Aug 16 2006 a minor update to the server has been implemented improving the prediction accuracy for MHC binding. The earlier version of the NetCTL 1.2 server (1.2 beta) is available via the versions history for the server.

View the version history of this server. All the previous versions are available on line, for comparison and reference.

The method integrates prediction of peptide MHC class I binding, proteasomal C terminal cleavage and TAP transport efficiency. The server allows for predictions of CTL epitopes restricted to 12 MHC class I supertype. MHC class I binding and proteasomal cleavage is performed using artificial neural networks. TAP transport efficiency is predictied using weight matrix.

The MHC peptide binding is predicted using neural networks trained as described for the NetMHC server. The proteasome cleavage event is predicted using the version of the NetChop neural networks trained on C terminals of known CTL epitopes as describe for the NetChop-3.0 server. The TAP transport efficiency is predicted using the weight matrix based method describe by Peters et al.

The server includes predictions of MHC/peptide binding for 12 MHC class I supertypes. The output from the neural network predicting MHC/peptide binding is a log transformed value related to the IC50 values in nM units. For details on the transformation please see output format.

The scores from the three individual prediction methods are integrated as a weighted sum with a relative weight on peptide/MHC binding of 1. Different thresholds for the integrated score can be translated into sensitivity/specificity values. In a large benchmark calculate containing more than 800 known MHC class I ligands the following relations were found

Score Sensitivity Specificity
> 1.25 0.54 0.993
> 1.00 0.70 0.985
> 0.90 0.74 0.980
> 0.75 0.80 0.970
> 0.50 0.89 0.940

The project is collaboration between CBS and IMMI.

Instructions Output format Data sets Article abstract


Paste a single sequence or several sequences in FASTA format into the field below:

Submit a file in FASTA format directly from your local disk:


Weight on C terminal cleavage         Weight on TAP transport efficiency         Threshold for epitope identification        

Sort by score  

At most 5000 sequences per submission; each sequence not more than 20,000 amino acids and not less than 9 amino acids for at most 200,000 amino acids in total.

The sequences are kept confidential and will be deleted after processing.


For publication of results, please cite:

  • Current version:

    Large-scale validation of methods for cytotoxic T-lymphocyte epitope prediction.
    Larsen MV, Lundegaard C, Lamberth K, Buus S, Lund O, Nielsen M.
    BMC Bioinformatics. Oct 31;8:424. 2007

    View the abstract        

  • Earlier versions:

    An integrative approach to CTL epitope prediction. A combined algorithm integrating MHC-I binding, TAP transport efficiency, and proteasomal cleavage predictions.
    Larsen M.V., Lundegaard C., Kasper Lamberth, Buus S,. Brunak S., Lund O., and Nielsen M.
    European Journal of Immunology. 35(8): 2295-303. 2005

    View the abstract        

  • Related publications:

    Reliable prediction of T-cell epitopes using neural networks with novel sequence representations.
    Nielsen M, Lundegaard C, Worning P, Lauemoller SL, Lamberth K, Buus S, Brunak S, Lund O.
    Protein Sci., 12:1007-17, 2003.

    View the abstract

    Sensitive quantitative predictions of peptide-MHC binding by a 'Query by Committee' artificial neural network approach.
    Buus S, Lauemoller SL, Worning P, Kesmir C, Frimurer T, Corbet S, Fomsgaard A, Hilden J, Holm A, Brunak S.
    Tissue Antigens., 62(5):378-84, 2003.

    View the abstract

    The role of the proteasome in generating cytotoxic T cell epitopes: Insights obtained from improved predictions of proteasomal cleavage.
    M. Nielsen, C. Lundegaard, S. Brunak, O. Lund, and C. Kesmir. Immunogenetics., 57(1-2):33-41, 2005.

    View the abstract

    Identifying MHC class I epitopes by predicting the TAP transport efficiency of epitope precursors
    Peters, B., Bulik, S., Tampe, R., Endert, P. M. V. and Holzhutter, H. G.
    J. Immunol. 171: 1741-1749, 2003.

    View the abstract



Would you prefer to run NetCTL at your own site? NetCTL 1.2 is available as a stand-alone software package, with the same functionality as the service above. Ready-to-ship packages exist for the most common UNIX platforms. There is a download page for academic users; other users are requested to contact CBS Software Package Manager at


Scientific problems:        Technical problems: