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• W2488256075 abstract "In this paper the insertion of the crowding-distance technique in a multiobjective genetic algorithm with phenotypic crowding is carried out for the protein structure prediction (PSP) problem. The main goal is obtain a more diversified and well distributed Pareto frontiers at the end of the optimization process. Three classical force field potentials, three hydrogen bond potentials and a hydrophobic compactation term were combined in two configurations with different objectives for the fitness function. A set of 45 proteins was used to evaluate the performance of the predictions. The results were compared against the previous mono- and multiobjective approaches, and with QUARK and MEAMT, two consolidated free-modeling PSP methodologies. The strategy proposed here was able to obtain improvements in the predicted models relative to the previous mono- and multiobjective approaches, proving to be quite promising in dealing with the PSP problem." @default.
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• W2488256075 date "2016-07-20" @default.
• W2488256075 modified "2023-09-25" @default.
• W2488256075 title "Using Crowding-Distance in a Multiobjective Genetic Algorithm for Protein Structure Prediction" @default.
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• W2488256075 doi "https://doi.org/10.1145/2908961.2931717" @default.
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