High-order neural networks and kernel methods for peptide-MHC binding prediction

Bioinformatics

Volumn 31, Issue 22, 2015, Pages 3600-3607

  Kuksa, Pavel P ^a,b   Min, Martin Renqiang ^b   Dugar, Rishabh ^b   Gerstein, Mark ^c,d  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b NEC LABORATORIES AMERICA   (United States)

^c YALE UNIVERSITY   (United States)

^d Yale University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EPITOPE; PEPTIDE; PROTEIN BINDING;

ALGORITHM; AMINO ACID SEQUENCE; AREA UNDER THE CURVE; ARTIFICIAL NEURAL NETWORK; CHEMISTRY; HUMAN; MAJOR HISTOCOMPATIBILITY COMPLEX; METABOLISM; MOLECULAR GENETICS; PROTEIN DATABASE; RECEIVER OPERATING CHARACTERISTIC; SUPPORT VECTOR MACHINE;

ALGORITHMS; AMINO ACID SEQUENCE; AREA UNDER CURVE; DATABASES, PROTEIN; EPITOPES; HUMANS; MAJOR HISTOCOMPATIBILITY COMPLEX; MOLECULAR SEQUENCE DATA; NEURAL NETWORKS (COMPUTER); PEPTIDES; PROTEIN BINDING; ROC CURVE; SUPPORT VECTOR MACHINE;

EID: 84947751854     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btv371     Document Type: Article

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