Large-scale computational identification of HIV T-cell epitopes

Immunology and Cell Biology

Volumn 80, Issue 3, 2002, Pages 300-306

  Schönbach, Christian ^a   Kun, Yu ^a   Brusic, Vladimir ^a  

^a INSTITUTE FOR INFOCOMM RESEARCH   (Singapore)

Author keywords

Artificial neural network; Epitope coverage; Hidden Markov model; HIV; HLA; Peptide; T cell epitope prediction

Indexed keywords

EPITOPE; GAG PROTEIN; HLA A ANTIGEN; HLA B ANTIGEN; POL PROTEIN; STRUCTURAL PROTEIN; VIRUS ENVELOPE PROTEIN; HUMAN IMMUNODEFICIENCY VIRUS ANTIGEN;

AMINO ACID SEQUENCE; ANALYTIC METHOD; ARTIFICIAL NEURAL NETWORK; BIOINFORMATICS; COMPUTER PROGRAM; DATA BASE; EPITOPE MAPPING; EVALUATION; HUMAN IMMUNODEFICIENCY VIRUS 1; HUMAN IMMUNODEFICIENCY VIRUS 2; INTERMETHOD COMPARISON; PREDICTION; REVIEW; T LYMPHOCYTE; VALIDATION PROCESS; ARTICLE; BIOLOGY; CHEMISTRY; COMPARATIVE STUDY; FORECASTING; HUMAN; HUMAN IMMUNODEFICIENCY VIRUS; IMMUNOLOGY; ISOLATION AND PURIFICATION; METHODOLOGY; MOLECULAR GENETICS; SENSITIVITY AND SPECIFICITY;

COMPARATIVE STUDY; COMPUTATIONAL BIOLOGY; EPITOPES, T-LYMPHOCYTE; FORECASTING; HIV; HIV ANTIGENS; HUMAN; MOLECULAR SEQUENCE DATA; SENSITIVITY AND SPECIFICITY; T-LYMPHOCYTES; HUMANS;

HUMAN IMMUNODEFICIENCY VIRUS; HUMAN IMMUNODEFICIENCY VIRUS 1; HUMAN IMMUNODEFICIENCY VIRUS 2; RNA VIRUSES;

EID: 0035989350     PISSN: 08189641     EISSN: None     Source Type: Journal    
DOI: 10.1046/j.1440-1711.2002.01089.x     Document Type: Review

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