On a matching distance between rooted phylogenetic trees

D. Bogdanowicz, K. Giaro
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引用次数: 44

Abstract

Abstract 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(n3/2)).
根系统发育树之间的匹配距离
Robinson-Foulds (RF)距离是评价系统发育树之间不相似性最常用的方法。在本文中,我们定义和探讨了匹配簇(MC)距离的详细性质,它可以看作是有根树的RF度量的改进。与RF类似,MC对比较树的聚类进行操作,但距离评估更为复杂。利用基于二部图最小权值完美匹配的图论方法,将聚类之间的相似度值转化为树之间不相似度的最终mc分数。通过对属性的分析,我们可以深入了解由MC生成的度量空间的结构、它与无根树的匹配分割(MS)距离的关系,以及在MC和MS中统一选择的二叉n叶树之间的期望距离的渐近行为(Θ(n3/2))。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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