Prediction of epitopes using neural network based methods

Claus Lundegaard, Ole Lund, Morten Nielsen

    Research output: Contribution to journalJournal articleResearchpeer-review

    Abstract

    In this paper, we describe the methodologies behind three different aspects of the NetMHC family for prediction of MHC class I binding, mainly to HLAs. We have updated the prediction servers, NetMHC-3.2, NetMHCpan-2.2, and a new consensus method, NetMHCcons, which, in their previous versions, have been evaluated to be among the very best performing MHC:peptide binding predictors available. Here we describe the background for these methods, and the rationale behind the different optimization steps implemented in the methods. We go through the practical use of the methods, which are publicly available in the form of relatively fast and simple web interfaces. Furthermore, we will review results obtained in actual epitope discovery projects where previous implementations of the described methods have been used in the initial selection of potential epitopes. Selected potential epitopes were all evaluated experimentally using ex vivo assays.
    Original languageEnglish
    JournalJournal of Immunological Methods
    Volume374
    Issue number1-2
    Pages (from-to)26-34
    ISSN0022-1759
    DOIs
    Publication statusPublished - 2011

    Keywords

    • Prediction
    • T cell
    • Epitope
    • Discovery
    • Binding
    • MHC

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