Toward the prediction of class I and II mouse major histocompatibility complex-peptide-binding affinity: in silico bioinformatic step-by-step guide using quantitative structure-activity relationships.

Methods in molecular biology (Clifton, N.J.)

Volumn 409, Issue , 2007, Pages 227-245

  Hattotuwagama, Channa K ^a   Doytchinova, Irini A ^a   Flower, Darren R ^a  

^a UNIVERSITY OF OXFORD   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

EPITOPE; H2 ANTIGEN; HLA ANTIGEN CLASS 1; HLA ANTIGEN CLASS 2; PEPTIDE;

ALGORITHM; ALLELE; ANIMAL; ARTICLE; BIOLOGY; CHEMICAL STRUCTURE; CHEMISTRY; COMPUTER PROGRAM; COMPUTER SIMULATION; GENETICS; IMMUNOGENETICS; IMMUNOLOGY; MAJOR HISTOCOMPATIBILITY COMPLEX; METABOLISM; MOUSE; PROTEIN BINDING; PROTEIN DATABASE; QUANTITATIVE STRUCTURE ACTIVITY RELATION;

ALGORITHMS; ALLELES; ANIMALS; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; DATABASES, PROTEIN; EPITOPES; H-2 ANTIGENS; HISTOCOMPATIBILITY ANTIGENS CLASS I; HISTOCOMPATIBILITY ANTIGENS CLASS II; IMMUNOGENETICS; MAJOR HISTOCOMPATIBILITY COMPLEX; MICE; MODELS, MOLECULAR; PEPTIDES; PROTEIN BINDING; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; SOFTWARE;

MLCS; MLOWN;

EID: 44649192502     PISSN: 10643745     EISSN: None     Source Type: Journal    
DOI: 10.1007/978-1-60327-118-9_16     Document Type: Article

References (0)