Use of a novel Hill-climbing genetic algorithm in protein folding simulations

Computational Biology and Chemistry

Volumn 27, Issue 6, 2003, Pages 575-580

  Cooper, Lee R ^a   Corne, David W ^a   Crabbe, M James C ^a  

^a UNIVERSITY OF READING   (United Kingdom)

Author keywords

Crambin; Fitness function; GA; Gamma crystallin; Supercomputer

Indexed keywords

CHROMOSOMES; COMPUTER SIMULATION; GENETIC ALGORITHMS; HYDROPHOBICITY; POLYPEPTIDES; PROTEINS; SUPERCOMPUTERS;

FITNESS FUNCTION; GAMMA CRYSTALLIN;

COMPUTATIONAL METHODS;

EID: 0344513150     PISSN: 14769271     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1476-9271(03)00047-1     Document Type: Note

References (6)

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4. Dandekar T., Argos P. Identifying the tertiary fold of small proteins with different topologies from sequence and secondary structure using the genetic algorithm and extended criteria specific for strand regions. J. Mol. Biol. 256:1996;645-660.
5. Goldberg, D.E., 1989. Genetic Algorithm in Search, Optimization, and Machine Learning. Addison-Wesley, New York.
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