Prediction of peptides binding to MHC class I and II alleles by temporal motif mining

BMC Bioinformatics

Volumn 14, Issue , 2013, Pages

  Meydan, Cem ^a   Otu, Hasan H ^b,c   Sezerman, Osman Uğur ^a  

^a SABANCI UNIVERSITY   (Turkey)

^b HARVARD MEDICAL SCHOOL   (United States)

^c ISTANBUL BILGI UNIVERSITY   (Turkey)

Author keywords

[No Author keywords available]

Indexed keywords

DNA SEQUENCES; GENES; IMMUNE SYSTEM; LEARNING SYSTEMS; MINING; PEPTIDES;

ANTIGENIC PEPTIDES; COMPUTATIONAL PREDICTIONS; MACHINE LEARNING METHODS; MAJOR HISTOCOMPATIBILITY COMPLEX; PERIODIC PATTERN; PREDICTION METHODS; SEQUENCE LENGTHS; STATE-OF-THE-ART METHODS;

FORECASTING;

VERTEBRATA;

PEPTIDE;

ALGORITHM; ALLELE; AREA UNDER THE CURVE; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; DATA MINING; GENE; HUMAN; METABOLISM; METHODOLOGY; PROTEIN BINDING; PROTEIN DATABASE; PROTEIN DOMAIN;

ALGORITHMS; ALLELES; AREA UNDER CURVE; ARTIFICIAL INTELLIGENCE; DATA MINING; DATABASES, PROTEIN; GENES, MHC CLASS I; GENES, MHC CLASS II; HUMANS; NEURAL NETWORKS (COMPUTER); PEPTIDES; PROTEIN BINDING; PROTEIN INTERACTION DOMAINS AND MOTIFS;

EID: 84884193260     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-14-S2-S13     Document Type: Article

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