Protein structure prediction using bee colony optimization metaheuristic
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Protein structure prediction using bee colony optimization metaheuristic. / Fonseca, Rasmus; Paluszewski, Martin; Winter, Pawel.
I: Journal of Mathematical Modelling and Algorithms, Bind 9, Nr. 2, 2010, s. 181-194.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Protein structure prediction using bee colony optimization metaheuristic
AU - Fonseca, Rasmus
AU - Paluszewski, Martin
AU - Winter, Pawel
PY - 2010
Y1 - 2010
N2 - Predicting the native structure of proteins is one of the most challenging problems in molecular biology. The goal is to determine the three-dimensional struc- ture from the one-dimensional amino acid sequence. De novo prediction algorithms seek to do this by developing a representation of the proteins structure, an energy potential and some optimization algorithm that ¿nds the structure with minimal energy.Bee Colony Optimization (BCO) is a relatively new approach to solving opti- mization problems based on the foraging behaviour of bees. Several variants of BCO have been suggested in the literature. We have devised a new variant that uni¿es the existing and is much more ¿exible with respect to replacing the various elements of the BCO. In particular this applies to the choice of the local search as well as the method for generating scout locations and performing the waggle dance. We apply our BCO method to generate good solutions to the protein structure prediction problem. The results show that BCO generally ¿nds better solutions than simulated annealing which so far has been the metaheuristic of choice for this problem.
AB - Predicting the native structure of proteins is one of the most challenging problems in molecular biology. The goal is to determine the three-dimensional struc- ture from the one-dimensional amino acid sequence. De novo prediction algorithms seek to do this by developing a representation of the proteins structure, an energy potential and some optimization algorithm that ¿nds the structure with minimal energy.Bee Colony Optimization (BCO) is a relatively new approach to solving opti- mization problems based on the foraging behaviour of bees. Several variants of BCO have been suggested in the literature. We have devised a new variant that uni¿es the existing and is much more ¿exible with respect to replacing the various elements of the BCO. In particular this applies to the choice of the local search as well as the method for generating scout locations and performing the waggle dance. We apply our BCO method to generate good solutions to the protein structure prediction problem. The results show that BCO generally ¿nds better solutions than simulated annealing which so far has been the metaheuristic of choice for this problem.
KW - Faculty of Science
KW - Protein Struktur Forudsigelse
KW - Bee Colony Optimization
KW - Metaheuristik
KW - Protein Structure Prediction
KW - Bee Colony Optimization
KW - Metaheuristic
U2 - 10.1007/s10852-010-9125-1
DO - 10.1007/s10852-010-9125-1
M3 - Journal article
VL - 9
SP - 181
EP - 194
JO - Journal of Mathematical Modelling and Algorithms in Operations Research
JF - Journal of Mathematical Modelling and Algorithms in Operations Research
SN - 2214-2487
IS - 2
ER -
ID: 14880974