Hidden Markov model-based prediction of antigenic peptides that interact with MHC class II molecules

Journal of Bioscience and Bioengineering

Volumn 94, Issue 3, 2002, Pages 264-270

  Noguchi, Hideki ^a   Kato, Ryuji ^a   Hanai, Taizo ^a   Matsubara, Yukari ^a   Honda, Hiroyuki ^a   Brusic, Vladimir ^b   Kobayashi, Takeshi ^a  

^a NAGOYA UNIVERSITY   (Japan)

^b Lab for Information Technology   (Singapore)

Author keywords

Binding peptides; Bioinformatics; Hidden Markov model; MHC class II; Successive state splitting

Indexed keywords

ANTIGENS; DATA RECORDING; HISTOLOGY; NEURAL NETWORKS; OPTIMIZATION;

PEPTIDE BINDERS;

IMMUNOLOGY;

ANTIGEN; MAJOR HISTOCOMPATIBILITY ANTIGEN CLASS 2; PEPTIDE DERIVATIVE;

ACCURACY; ALGORITHM; ANTIGEN BINDING; ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOINFORMATICS; HIDDEN MARKOV MODEL; INTERMETHOD COMPARISON; MAJOR HISTOCOMPATIBILITY COMPLEX; PEPTIDE ANALYSIS; PREDICTION; PROBABILITY; RECEIVER OPERATING CHARACTERISTIC; RELATIVE OPERATING CHARACTERISTIC; STATISTICAL MODEL;

EID: 0036399733     PISSN: 13891723     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1389-1723(02)80160-8     Document Type: Article

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