Optimization Over a Class of Tree Shape Statistics
Optimization Over a Class of Tree Shape Statistics
复制标题
一类树形统计的优化
DOI：
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发表时间：
2006
期刊：
影响因子：
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通讯作者：
Frederick Albert Matsen IV
中科院分区：
文献类型：
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作者：
Frederick Albert Matsen IV
树形状统计量化系统发育树形状的某些方面。它们通常用于将重建的树与进化模型进行比较，并寻找树重建偏差的证据。从历史上看，为了找到有用的树形统计数据，人们需要手工发明公式，然后评估其实用性。本文提出了第一种能够优化一类树形状统计的方法，称为二叉递归树形状统计（BRTSS）。定义 BRTSS 类后，定义了一组可在递归中使用的代数表达式。在 BRTSS 中使用这些表达式定义的树形状统计数据集非常通用，并且包括系统发生研究人员已经熟悉的许多统计数据。然后，我们提出了一种实用的遗传算法，它能够在给定任何目标函数的情况下对 BRTSS 进行优化。本章最后成功地应用了这些方法来寻找新的统计数据，该统计数据表明先前假设具有相似属性的树上的两个分布之间存在显着差异。
Tree shape statistics quantify some aspect of the shape of a phylogenetic tree. They are commonly used to compare reconstructed trees to evolutionary models and to find evidence of tree reconstruction bias. Historically, to find a useful tree shape statistic, formulas have been invented by hand and then evaluated for utility. This paper presents the first method which is capable of optimizing over a class of tree shape statistics, called binary recursive tree shape statistics (BRTSS). After defining the BRTSS class, a set of algebraic expressions is defined which can be used in the recursions. The set of tree shape statistics definable using these expressions in the BRTSS is very general and includes many of the statistics with which phylogenetic researchers are already familiar. We then present a practical genetic algorithm which is capable of performing optimization over BRTSS given any objective function. The chapter concludes with a successful application of the methods to find a new statistic which indicates a significant difference between two distributions on trees which were previously postulated to have similar properties.
DOI：
10.1073/pnas.0409515102
发表时间：
2005-03-01
影响因子：
11.1
作者：
Middendorf, M;Ziv, E;Wiggins, CH
通讯作者：
Wiggins, CH