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arXiv 0810.0868q-bio.PEq-bio.QM
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计算树度量的分布

Computing the Distribution of a Tree Metric

David Bryant, Mike Steel

摘要:

Robinson-Foulds(RF)距离是迄今为止最广泛使用的树之间的相异性度量。虽然这些距离的分布已经被研究了20年,但还没有一个明确的多项式时间算法来计算这个分布(这也是在流行的Robinson-Foulds度量下给定树周围的树的分布)。在本文中,我们推导出一个多项式时间算法,这种分布。我们展示了如何分布可以近似泊松分布确定的比例,躺在'樱桃'的给定树的叶子。我们还描述了如何我们的结果可以用来推导出所需的归一化常数,在最近提出的最大似然法超树建设。

英文摘要:

The Robinson-Foulds (RF) distance is by far the most widely used measure of dissimilarity between trees. Although the distribution of these distances has been investigated for twenty years, an algorithm that is explicitly polynomial time has yet to be described for computing this distribution (which is also the distribution of trees around a given tree under the popular Robinson-Foulds metric). In this paper we derive a polynomial-time algorithm for this distribution. We show how the distribution can be approximated by a Poisson distribution determined by the proportion of leaves that lie in `cherries' of the given tree. We also describe how our results can be used to derive normalization constants that are required in a recently-proposed maximum likelihood approach to supertree construction.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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