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Analyzing sets of phylogenetic trees using metrics

100%
Bogdanowicz D.
Applicationes Mathematicae
|
2011
|
tom 38
|
nr 1
1-16
EN
The reconstruction of evolutionary trees is one of the primary objectives in phylogenetics. Such a tree represents historical evolutionary relationships between different species or organisms. Tree comparisons are used for multiple purposes, from unveiling the history of species to deciphering evolutionary associations among organisms and geographical areas. In this paper, we describe a general method for comparing phylogenetic trees and give some basic properties of the Matching Split metric, which is a special case of a general definition. We focus on four metrics for binary unrooted trees. We present results of a computational experiment concerning an application of those metrics to estimating the quality of a phylogenetic signal.
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On a matching distance between rooted phylogenetic trees

63%
Bogdanowicz D., Giaro K.
International Journal of Applied Mathematics and Computer Science
|
2013
|
tom 23
|
nr 3
669-684
EN
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})).
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