A gradient-directed Monte Carlo method for global optimization in a discrete space: Application to protein sequence design and folding

Journal of Chemical Physics

Volumn 131, Issue 15, 2009, Pages

  Hu, Xiangqian ^a   Beratan, David N ^a   Yang, Weitao ^a  

^a DUKE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACTUAL SYSTEM; ATOMIC POTENTIAL; CHEMICAL VARIABLES; DERIVATIVE INFORMATION; DISCRETE SPACES; DISCRETE VALUES; GLOBAL MINIMA; HP LATTICE; LINEAR COMBINATIONS; LOCAL MINIMUMS; LOCAL PROPERTY; METROPOLIS CRITERION; MODEL HAMILTONIANS; MOLECULAR DESIGN; MONTE CARLO; MONTE CARLO APPROACH; OTHER DISCRETE; PROPERTY VALUE; PROTEIN SEQUENCE DESIGN; PROTEIN SEQUENCES;

GLOBAL OPTIMIZATION; INVERSE PROBLEMS; MONTE CARLO METHODS; OPTIMIZATION;

PROTEIN FOLDING;

PROTEIN;

ARTICLE; CHEMISTRY; MONTE CARLO METHOD; PROTEIN FOLDING;

MONTE CARLO METHOD; PROTEIN FOLDING; PROTEINS;

EID: 70449346605     PISSN: 00219606     EISSN: None     Source Type: Journal    
DOI: 10.1063/1.3236834     Document Type: Article

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