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ON A MATCHING DISTANCE BETWEEN ROOTED PHYLOGENETIC TREES

机译:植根生根树之间的匹配距离

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The Robinson-Foulds (RF) distance is the most popular method of evaluating the dissimilarity between phylogenetic trees. In this paper, we define and explore in detail properties of the Matching Cluster (MC) distance, which can be regarded as a refinement of the RF metric for rooted trees. Similarly to RF, MC operates on clusters of compared trees, but the distance evaluation is more complex. Using the graph theoretic approach based on a minimum-weight perfect matching in bipartite graphs, the values of similarity between clusters are transformed to the final MC-score of the dissimilarity of trees. The analyzed properties give insight into the structure of the metric space generated by MC, its relations with the Matching Split (MS) distance of unrooted trees and asymptotic behavior of the expected distance between binary n-leaf trees selected uniformly in both MC and MS (Θ(n~(3/2))).
机译:Robinson-Foulds(RF)距离是评估系统发生树之间差异的最流行方法。在本文中,我们定义并详细研究了匹配簇(MC)距离的属性,可以将其视为对生根树的RF度量的改进。与RF相似,MC在比较树的群集上运行,但是距离评估更为复杂。使用基于二元图中最小权重完美匹配的图论方法,将聚类之间的相似度值转换为树的相似度的最终MC评分。分析后的属性可以深入了解MC生成的度量空间的结构,其与无根树的匹配拆分(MS)距离的关系以及在MC和MS中均等选择的二元n叶树之间的预期距离的渐近行为( Θ(n〜(3/2)))。

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