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首页> 外文期刊>Biophysical Chemistry: An International Journal Devoted to the Physical Chemistry of Biological Phenomena >A GENETIC ALGORITHM TO SEARCH FOR OPTIMAL AND SUBOPTIMAL RNA SECONDARY STRUCTURES
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A GENETIC ALGORITHM TO SEARCH FOR OPTIMAL AND SUBOPTIMAL RNA SECONDARY STRUCTURES

机译:寻找最佳和次最佳RNA二级结构的遗传算法

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摘要

Genetic algorithms are a search method used in solving problems by selection, recombination and mutation of tentative solutions, until the better ones are achieved. They are very efficient when the 'building block' hypothesis is effective for the solutions, which means that a better solution can be obtained by assembling short 'motifs' or 'schemata' that can be retrieved in some other worse solutions. The additive nature of the secondary structure free energy rules suggests the validity of this hypothesis, and therefore the likely power of a genetic algorithm approach to search for RNA secondary structures. We describe in detail an original genetic algorithm specific for this problem. The sharing function used to obtain differentiated solutions is also described. It results in a greater effectiveness of the algorithm in retrieving a large number of suboptimal RNA foldings besides the optimal one. RNA sequences of different length are used to test the method. The PSTV viroid sequence has been studied. [References: 23]
机译:遗传算法是一种搜索方法,用于通过对暂定解的选择,重组和突变来解决问题,直到获得更好的解。当“基本要素”假设对解决方案有效时,它们非常有效,这意味着可以通过组合可以在其他一些较差的解决方案中找到的简短“图案”或“方案”来获得更好的解决方案。二级结构自由能规则的累加性质表明了该假设的有效性,因此也证明了遗传算法搜索RNA二级结构的可能性。我们将详细描述针对此问题的原始遗传算法。还描述了用于获得差分解的共享函数。除了获得最佳算法之外,该算法在检索大量次优RNA折叠中具有更高的有效性。使用不同长度的RNA序列来测试该方法。已经研究了PSTV类病毒序列。 [参考:23]

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