Please use this identifier to cite or link to this item: https://doi.org/10.1093/nar/gki452
Title: MULTIPRED: A computational system for prediction of promiscuous HLA binding peptides
Authors: Zhang, G.L.
Khan, A.M.
Srinivasan, K.N. 
August, J.T. 
Brusic, V. 
Issue Date: Jul-2005
Citation: Zhang, G.L., Khan, A.M., Srinivasan, K.N., August, J.T., Brusic, V. (2005-07). MULTIPRED: A computational system for prediction of promiscuous HLA binding peptides. Nucleic Acids Research 33 (SUPPL. 2) : W172-W179. ScholarBank@NUS Repository. https://doi.org/10.1093/nar/gki452
Abstract: MULTIPRED is a web-based computational system for the prediction of peptide binding to multiple molecules (proteins) belonging to human leukocyte antigens (HLA) class I A2, A3 and class II DR supertypes. It uses hidden Markov models and artificial neural network methods as predictive engines. A novel data representation method enables MULTIPRED to predict peptides that promiscuously bind multiple HLA alleles within one HLA supertype. Extensive testing was performed for validation of the prediction models. Testing results show that MULTIPRED is both sensitive and specific and it has good predictive ability (area under the receiver operating characteristic curve A ROC > 0.80). MULTIPRED can be used for the mapping of promiscuous T-cell epitopes as well as the regions of high concentration of these targets - termed T-cell epitope hotspots. MULTIPRED is available at http://antigen.i2r.a-star.edu.sg/ multipred/. © 2005 Oxford University Press.
Source Title: Nucleic Acids Research
URI: http://scholarbank.nus.edu.sg/handle/10635/107738
ISSN: 03051048
DOI: 10.1093/nar/gki452
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