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使用启发式算法进行翻转超树构建的性能

Performance of flip supertree construction with a heuristic algorithm.

作者信息

Eulenstein Oliver, Chen Duhong, Burleigh J Gordon, Fernández-Baca David, Sanderson Michael J

机构信息

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

出版信息

Syst Biol. 2004 Apr;53(2):299-308. doi: 10.1080/10635150490423719.

Abstract

Supertree methods are used to assemble separate phylogenetic trees with shared taxa into larger trees (supertrees) in an effort to construct more comprehensive phylogenetic hypotheses. In spite of much recent interest in supertrees, there are still few methods for supertree construction. The flip supertree problem is an error correction approach that seeks to find a minimum number of changes (flips) to the matrix representation of the set of input trees to resolve their incompatibilities. A previous flip supertree algorithm was limited to finding exact solutions and was only feasible for small input trees. We developed a heuristic algorithm for the flip supertree problem suitable for much larger input trees. We used a series of 48- and 96-taxon simulations to compare supertrees constructed with the flip supertree heuristic algorithm with supertrees constructed using other approaches, including MinCut (MC), modified MC (MMC), and matrix representation with parsimony (MRP). Flip supertrees are generally far more accurate than supertrees constructed using MC or MMC algorithms and are at least as accurate as supertrees built with MRP. The flip supertree method is therefore a viable alternative to other supertree methods when the number of taxa is large.

摘要

超树方法用于将具有共享分类群的单独系统发育树组装成更大的树(超树),以便构建更全面的系统发育假说。尽管最近对超树有很多关注,但用于构建超树的方法仍然很少。翻转超树问题是一种纠错方法,旨在找到对输入树集的矩阵表示进行最少次数的更改(翻转),以解决它们之间的不兼容性。先前的翻转超树算法仅限于找到精确解,并且仅适用于小的输入树。我们为翻转超树问题开发了一种启发式算法,适用于大得多的输入树。我们使用了一系列包含48个和96个分类群的模拟,将使用翻转超树启发式算法构建的超树与使用其他方法构建的超树进行比较,这些方法包括最小割(MC)、改进的MC(MMC)和简约法矩阵表示(MRP)。翻转超树通常比使用MC或MMC算法构建的超树准确得多,并且至少与使用MRP构建的超树一样准确。因此,当分类群数量很大时,翻转超树方法是其他超树方法的可行替代方案。

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