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用于基因复制问题的TBR启发式算法的Ω(n²/log n)加速比。

An Omega(n2/ log n) speed-up of TBR heuristics for the gene-duplication problem.

作者信息

Bansal Mukul S, Eulenstein Oliver

机构信息

Department of Computer Science, Iowa State University, Ames, IA 50011, USA.

出版信息

IEEE/ACM Trans Comput Biol Bioinform. 2008 Oct-Dec;5(4):514-24. doi: 10.1109/TCBB.2008.69.

Abstract

The gene-duplication problem is to infer a species supertree from gene trees that are confounded by complex histories of gene duplications. This problem is NP-hard and thus requires efficient and effective heuristics. Existing heuristics perform a stepwise search of the tree space, where each step is guided by an exact solution to an instance of a local search problem. We improve on the time complexity of the local search problem by a factor of n2= log n, where n is the size of the resulting species supertree. Typically, several thousand instances of the local search problem are solved throughout a stepwise heuristic search. Hence, our improvement makes the gene-duplication problem much more tractable for large-scale phylogenetic analyses.

摘要

基因复制问题是要从因复杂的基因复制历史而混淆的基因树中推断出物种超树。这个问题是NP难问题,因此需要高效且有效的启发式算法。现有的启发式算法对树空间进行逐步搜索,其中每一步都由局部搜索问题实例的精确解来引导。我们将局部搜索问题的时间复杂度提高了n2 = log n倍,其中n是所得物种超树的规模。通常,在逐步启发式搜索过程中要解决数千个局部搜索问题实例。因此,我们的改进使得基因复制问题在大规模系统发育分析中更易于处理。

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