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A tabu search algorithm for maximum parsimony phylogeny inference

机译:禁忌搜索算法,用于最大简约系统发育推断

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Phylogeny reconstruction is too complex a combinatorial problem for an exhaustive search, because the number of possible solutions increases exponentially with the number of taxa involved. In this paper, we adopt the parsimony principle and design a tabu search algorithm for finding a most parsimonious phylogeny tree. A special array structure is employed to represent the topology of trees and to generate the neighboring trees. We test the proposed tabu search algorithm on randomly selected data sets obtained from nuclear ribosomal DNA sequence data. The experiments show that our algorithm explores fewer trees to reach the optimal one than the commonly used program "dnapenny" (branch-and-bound based) while it generates much more accurate results than the default options of the program "dnapars" (heuristic search based). The percentage of search space needed to find the best solution for our algorithm decreased rapidly as the number of taxa increased. For a 20-taxon phylogeny problem, it needs on average to examine only 3.92 x 10(-15)% of the sample space. (c) 2005 Elsevier B.V. All rights reserved.
机译:系统发育重建对于详尽的搜索而言是一个过于复杂的组合问题,因为可能的解决方案的数量会随着所涉及的分类单元的数量呈指数增长。在本文中,我们采用简约原则,设计了禁忌搜索算法来查找最简约的系统进化树。采用特殊的阵列结构来表示树的拓扑并生成相邻的树。我们在从核糖体DNA序列数据中随机选择的数据集上测试了建议的禁忌搜索算法。实验表明,与常用程序“ dnapenny”(基于分支绑定)相比,我们的算法探索的树木更少,从而可以达到最佳树,而与程序“ dnapars”(启发式搜索)的默认选项相比,它生成的结果要准确得多基于)。随着分类单元数量的增加,为我们的算法找到最佳解决方案所需的搜索空间百分比迅速下降。对于20类分类系统发育问题,平均只需要检查样本空间的3.92 x 10(-15)%。 (c)2005 Elsevier B.V.保留所有权利。

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