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- W2890824192 abstract "The protein structure prediction (PSP) problem, i.e., predicting the three-dimensional structure of a protein from its sequence, remains challenging in computational biology. The inaccuracy of existing protein energy functions and the huge conformation search space make the problem difficult to solve. In this study, the PSP problem is modeled as a multi-objective optimization problem. A physics-based energy function and a knowledge-based energy function are combined to construct the three-objective energy function. An improved multi-objective particle swarm optimization coupled with two archives is employed to execute the conformation space search. In addition, a mechanism based on Pareto non-dominated sorting is designed to properly address the slightly worse solutions. Finally, the experimental results demonstrate the effectiveness of the proposed approach. A new perspective for solving the PSP problem by means of multi-objective optimization is given in this paper." @default.
- W2890824192 created "2018-09-27" @default.
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- W2890824192 date "2018-11-01" @default.
- W2890824192 modified "2023-10-14" @default.
- W2890824192 title "Adoption of an improved PSO to explore a compound multi-objective energy function in protein structure prediction" @default.
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- W2890824192 doi "https://doi.org/10.1016/j.asoc.2018.07.042" @default.
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