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Open Access
|Sep 2013

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)).

DOI: https://doi.org/10.2478/amcs-2013-0050 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X
Language: English
Page range: 669 - 684
Published on: Sep 30, 2013
Published by: University of Zielona Góra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 times per year

© 2013 Damian Bogdanowicz, Krzysztof Giaro, published by University of Zielona Góra
This work is licensed under the Creative Commons License.