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A Solution to Protein Folding Problem Using a Genetic Algorithm with Modified Keep Best Reproduction Strategy

机译:使用改进的遗传算法对蛋白质折叠问题的解决方案

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Genetic algorithms have proved to be a successful method for predicting the protein structure. In this paper, we propose a new intermediate selection strategy for genetic algorithms and we implement it for protein folding problem. In a standard genetic algorithm the children replace their parents. The idea behind this is that both parents pass on their good genetic material to their children. In practice however, children can have worse fitness than their parents. We therefore propose another intermediate selection step, which we call as modified keep-best reproduction (MKBR) that ensures that new genetic information is entered into the gene pool, as well as good previous genetic material is being preserved. We have demonstrated the superiority of modified keep-best reproduction on several instances of the protein-folding problem, which not only finds the optimum solution, but also finds them faster than the standard generational replacement schemes.
机译:已经证明了遗传算法是预测蛋白质结构的成功方法。在本文中,我们为遗传算法提出了一种新的中间选择策略,我们为蛋白质折叠问题实施了它。在标准遗传算法中,孩子们更换父母。这背后的想法是,父母双方都将他们的良好遗传物质传递给他们的孩子。然而,在实践中,儿童可能比父母更糟糕。因此,我们提出了另一种中间选择步骤,我们称之为修改的保持最佳再现(MKBR),确保新的遗传信息进入基因库,以及良好的先前遗传物质被保存。我们已经证明了在蛋白质折叠问题的几个实例上进行了修改的保持最佳繁殖的优越性,这不仅找到了最佳解决方案,而且还要速度比标准的世代替代方案快。

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