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[混沌人工蜂群算法:一种解决三维蛋白质结构能量最小化问题的新方法]

[Chaotic artificial bee colony algorithm: a new approach to the problem of minimization of energy of the 3D protein structure].

作者信息

Wang Y, Guo G D, Chen L F

出版信息

Mol Biol (Mosk). 2013 Nov-Dec;47(6):1020-7.

Abstract

Frediction of the three-dimensional structure of a protein from its amino acid sequence can be considered as a global optimization problem. In this paper, the Chaotic Artificial Bee Colony (CABC) algorithm was introduced and applied to 3D protein structure prediction. Based on the 3D off-lattice AB model, the CABC algorithm combines global search and local search of the Artificial Bee Colony (ABC) algorithm with the Chaotic search algorithm to avoid the problem of premature convergence and easily trapping the local optimum solution. The experiments carried out with the popular Fibonacci sequences demonstrate that the proposed algorithm provides an effective and high-performance method for protein structure prediction.

摘要

从蛋白质的氨基酸序列预测其三维结构可被视为一个全局优化问题。本文介绍了混沌人工蜂群(CABC)算法并将其应用于三维蛋白质结构预测。基于三维非晶格AB模型,CABC算法将人工蜂群(ABC)算法的全局搜索和局部搜索与混沌搜索算法相结合,以避免过早收敛和容易陷入局部最优解的问题。使用流行的斐波那契序列进行的实验表明,该算法为蛋白质结构预测提供了一种有效且高性能的方法。

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