Hidden Markov models that use predicted local structure for fold recognition: Alphabets of backbone geometry

Proteins: Structure, Function and Genetics

Volumn 51, Issue 4, 2003, Pages 504-514

  Karchin, Rachel ^a   Cline, Melissa ^b   Mandel Gutfreund, Yael ^c   Karplus, Kevin ^a  

^a University of California Santa Cruz   (United States)

^b Thermo Fisher Scientific   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Alignment; Information theory; Multitrack HMM; Neural network; Protein structure prediction; Secondary structure; Two track HMM

Indexed keywords

PROTEIN;

ARTICLE; PRIORITY JOURNAL; PROBABILITY; PROTEIN FOLDING; PROTEIN SECONDARY STRUCTURE; PROTEIN STRUCTURE; ROC CURVE; SEQUENCE ALIGNMENT; SEQUENCE HOMOLOGY;

ALGORITHMS; COMPUTATIONAL BIOLOGY; MARKOV CHAINS; PROTEIN FOLDING; PROTEIN STRUCTURE, SECONDARY; PROTEINS; REPRODUCIBILITY OF RESULTS; SEQUENCE ALIGNMENT;

EID: 0038278386     PISSN: 08873585     EISSN: None     Source Type: Journal    
DOI: 10.1002/prot.10369     Document Type: Article

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