A strategy for the identification of canonical and non-canonical MHC I-binding epitopes using an ANN-based epitope prediction algorithm

QSAR and Combinatorial Science

Volumn 25, Issue 4, 2006, Pages 350-358

  Filter, Matthias ^a   Eichler Mertens, Mathias ^a   Bredenbeck, Anne ^a   Losch, Florian O ^a   Sharav, Tumenjargal ^a   Givehchi, Alireza ^b   Walden, Peter ^a   Wrede, Paul ^a  

^a CHARITÉ UNIVERSITÄTSMEDIZIN BERLIN   (Germany)

^b GOETHE UNIVERSITY   (Germany)

Author keywords

Epitope prediction; HLA A*0201; Melanoma; MHC ligands; Neural networks

Indexed keywords

CELL MEMBRANES; CYTOLOGY; DERMATOLOGY; DNA SEQUENCES; EPITOPES; FORECASTING; GENES; ONCOLOGY; PEPTIDES; T-CELLS;

CLASS I; EPITOPE PREDICTIONS; HLA-A*0201; MAJOR HISTOCOMPATIBILITY COMPLEX; MAJOR HISTOCOMPATIBILITY COMPLEX CLASS; MAJOR HISTOCOMPATIBILITY COMPLEX LIGAND; MELANOMA; NETWORK-BASED; NEURAL-NETWORKS; T-CELL EPITOPES;

NEURAL NETWORKS;

EPITOPE; HLA A ANTIGEN; MAJOR HISTOCOMPATIBILITY ANTIGEN CLASS 1;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; CLINICAL ARTICLE; CONTROLLED STUDY; HUMAN; HUMAN CELL; MELANOMA; PHYLOGENY; PREDICTION; PRIORITY JOURNAL; PROTEIN FAMILY; SENSITIVITY ANALYSIS;

EID: 33646240348     PISSN: 1611020X     EISSN: 16110218     Source Type: Journal    
DOI: 10.1002/qsar.200510154     Document Type: Article

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