Computing the distribution of a tree metric

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dc.contributor.authorBryant, D.
dc.contributor.authorSteel, M.
dc.date.accessioned2009-09-03T02:17:18Z
dc.date.available2009-09-03T02:17:18Z
dc.date.issued2009en
dc.description.abstractThe Robinson-Foulds (RF) distance is by far the most widely used measure of dissimilarity between trees. Although the distribution of these distances has been investigated for twenty years, an algorithm that is explicitly polynomial time has yet to be described for computing this distribution (which is also the dis- tribution of trees around a given tree under the popular Robinson-Foulds metric). In this paper we derive a polynomial-time algorithm for this distribution. We show how the distribution can be approximated by a Poisson distribution determined by the proportion of leaves that lie in ‘cherries’ of the given tree. We also describe how our results can be used to derive normalization constants that are required in a recently-proposed maximum likelihood approach to supertree construction.en
dc.identifier.citationBryant, D., Steel, M. (2009) Computing the distribution of a tree metric. IEEE/ACM Transactions in Computational Biology and Bioinformatics.en
dc.identifier.doihttps://doi.org/10.1109/TCBB.2009.32
dc.identifier.urihttp://hdl.handle.net/10092/2791
dc.language.isoen
dc.publisherUniversity of Canterbury. Mathematics and Statisticsen
dc.rights.urihttps://hdl.handle.net/10092/17651en
dc.subjectbiology and geneticsen
dc.subjectdiscrete mathematics applicationsen
dc.subjecttreesen
dc.subjectphylogeneticsen
dc.subjectRobinson-Foulds distanceen
dc.subjectPoisson approximationen
dc.subjectnormalization constanten
dc.subject.marsdenFields of Research::230000 Mathematical Sciences::230200 Statistics::230204 Applied statisticsen
dc.subject.marsdenFields of Research::270000 Biological Sciences::270200 Geneticsen
dc.titleComputing the distribution of a tree metricen
dc.typeJournal Article
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