D
David Bryant
Researcher at University of Otago
Publications - 136
Citations - 19260
David Bryant is an academic researcher from University of Otago. The author has contributed to research in topics: Phylogenetic tree & Coalescent theory. The author has an hindex of 37, co-authored 136 publications receiving 16450 citations. Previous affiliations of David Bryant include Centre de Recherches Mathématiques & University of Auckland.
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Journal ArticleDOI
Application of Phylogenetic Networks in Evolutionary Studies
Daniel H. Huson,David Bryant +1 more
TL;DR: This article reviews the terminology used for phylogenetic networks and covers both split networks and reticulate networks, how they are defined, and how they can be interpreted and outlines the beginnings of a comprehensive statistical framework for applying split network methods.
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popart: full-feature software for haplotype network construction
Jessica W. Leigh,David Bryant +1 more
TL;DR: Popart is presented, an integrated software package that provides a comprehensive implementation of haplotype network methods, phylogeographic visualisation tools and standard statistical tests, together with publication‐ready figure production.
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NeighborNet: An Agglomerative Method for the Construction of Planar Phylogenetic Networks
David Bryant,Vincent Moulton +1 more
TL;DR: Neighbor-Net is presented, a distance based method for constructing phylogenetic networks that is based on the Neighbor-Joining (NJ) algorithm of Saitou and Nei and can quickly produce detailed and informative networks for several hundred taxa.
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A simple and robust statistical test for detecting the presence of recombination.
TL;DR: A new statistic, Φw, is developed that can be used to test for recombination and is suggested to be one of the best approaches to distinguish recurrent mutation from recombination in a wide variety of circumstances.
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Inferring Species Trees Directly from Biallelic Genetic Markers: Bypassing Gene Trees in a Full Coalescent Analysis
TL;DR: A polynomial-time algorithm that computes the likelihood of a species tree directly from the markers under a finite-sites model of mutation effectively integrating over all possible gene trees is described.