Prediction of peptide binding to major histocompatibility complex class II molecules through use of boosted fuzzy classifier with SWEEP operator method

Journal of Bioscience and Bioengineering

Volumn 101, Issue 2, 2006, Pages 137-141

  Takahashi, Hiro ^a   Honda, Hiroyuki ^a  

^a NAGOYA UNIVERSITY   (Japan)

Author keywords

binding peptides; bioinformatics; boosting; fuzzy theory; major histocompatibility complex (MHC) class II

Indexed keywords

CELLS; COMPUTER SIMULATION; FUZZY CONTROL; IMMUNOLOGY; MATHEMATICAL MODELS; MATHEMATICAL OPERATORS; MEDICAL PROBLEMS; NEURAL NETWORKS; POLYPEPTIDES; PROTEINS;

BINDING PEPTIDES; BIOINFORMATICS; BOOSTING; MAJOR HISTOCOMPATIBILITY COMPLEX (MHC) CLASS II;

GENETIC ENGINEERING;

MAJOR HISTOCOMPATIBILITY ANTIGEN CLASS 2; HLA ANTIGEN CLASS 2; PEPTIDE;

AMINO ACID SEQUENCE; ARTICLE; BINDING AFFINITY; HYDROPHOBICITY; INFORMATION PROCESSING; INTERMETHOD COMPARISON; MODEL; PREDICTION; PROTEIN BINDING; ARTIFICIAL NEURAL NETWORK; CHEMICAL STRUCTURE; CHEMISTRY; COMPARATIVE STUDY; FUZZY LOGIC; METABOLISM; PROTEIN CONFORMATION;

FUZZY LOGIC; HISTOCOMPATIBILITY ANTIGENS CLASS II; MODELS, MOLECULAR; NEURAL NETWORKS (COMPUTER); PEPTIDES; PROTEIN BINDING; PROTEIN CONFORMATION;

EID: 33745674976     PISSN: 13891723     EISSN: None     Source Type: Journal    
DOI: 10.1263/jbb.101.137     Document Type: Article

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