Protein conformational flexibility prediction using machine learning

Journal of Magnetic Resonance

Volumn 192, Issue 1, 2008, Pages 37-47

  Trott, Oleg ^a   Siggers, Keri ^a   Rost, Burkhard ^a   Palmer III, Arthur G ^a  

^a Columbia University ^*  (United States)

Author keywords

Fibronectin; FREAC 11; Generalized order parameter; Neural network; NMR; Relaxation; Tenascin

Indexed keywords

CONFORMATIONS; CORRELATION METHODS; NEURAL NETWORKS; PARAMETERIZATION; PROBABILITY; PROTEINS;

FIBRONECTIN; GENERALIZED ORDER PARAMETER; PEARSON'S CORRELATION COEFFICIENT; TENASCIN;

LEARNING SYSTEMS;

NITROGEN; PROTEIN;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CHEMISTRY; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE; PROTEIN CONFORMATION; PROTEIN SECONDARY STRUCTURE;

NEURAL NETWORKS (COMPUTER); NITROGEN ISOTOPES; NUCLEAR MAGNETIC RESONANCE, BIOMOLECULAR; PROTEIN CONFORMATION; PROTEIN STRUCTURE, SECONDARY; PROTEINS;

EID: 42749091409     PISSN: 10907807     EISSN: 10960856     Source Type: Journal    
DOI: 10.1016/j.jmr.2008.01.011     Document Type: Article

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