An updated version HLA-DR4Pred2 is available       TheHLA-DR4Pred is an SVM and ANN based HLA-DRB1*0401(MHC class II alleles) binding peptides prediction method. The accuracy of the SVM and ANN based methods is ~86% and ~78% respectively.The performence of the methods was tested through 5 set cross-validation. The training of SVM and ANN was done by using the freely availaible SVM_LIGHT and SNNS packages respectively. The data for training of neural network and SVM model has been extracted from MHCBN database.This method will be useful in cellular immunology, Vaccine design, immunodiagnostics, immunotherapeuatics and molecular understanding of autoimmune susceptibility.     Home Instructions Information References Developers         Name of Sequence[optional]     Paste Sequence     Or upload sequence file     Specify Sequence Format Amino acids in single letter code (plain text) Standard sequence format (PIR/FASTA/EMBL etc.)     Prediction Based on SVM     Threshold          ANN     Threshold        Tabular Display Display Top    10 50 100 200 500 1000   Peptides                      Dr. G P S Raghava Head, Department of Computational Biology Indraprastha Institute of Information Technology Okhla Phase 3, New Delhi, India Phone: +91-172-690557 +91-172-690908 Fax: +91-172-690585 +91-172-690632 Email: raghava@iiitd.ac.in

If you use this webserver please cite: Bhasin M, Raghava GPS (2004).SVM based method for predicting HLA-DRB1 binding peptides in an antigen sequence. Bioinformatics 20(3): 421-3