A phylogenetic tree represents historical evolutionary relationshipbetween different species or organisms. There are various methods for reconstructing phylogenetic trees.Applying those techniques usually results in different treesfor the same input data. An important problem is to determinehow distant two trees reconstructed in such a wayare from each other. Comparing phylogenetic trees is alsouseful in mining phylogenetic information...

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...

Ability to quantify dissimilarity of different phylogenetic trees describing the relationship between the same group of taxa is required in various types of phylogenetic studies. For example, such metrics are used to assess the quality of phylogeny construction methods, to define optimization criteria in supertree building algorithms, or to find horizontal gene transfer (HGT) events. Among the set of metrics described so far in...

In the paper, we describe a method for comparing arbitrary, not necessary fully resolved, unrooted phylogenetic trees. Proposed method is based on finding a minimum weight matching in bipartite graphs and can be regarded as a generalization of well-known Robinson-Foulds distance. We present some properties and advantages of the new distance. We also investigate some properties of presented distance in a common biological problem...

the following paper presents a new polynomial time metric for unrootedphylogenetic trees (based on weighted bipartite graphs and the method ofdetermining a minimum perfect matching) and its properties. also many its properties are presented.