Who is Who in Phylogenetic Networks

Publications related to 'quasi-median network' : A quasi-median network is the generalisation of a median network where characters can have more than two states   Order by:   Type | Year

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abstract-network from-sequences median-network parsimony phylogenetic-network phylogeny polynomial Program-QuasiDec quasi-median-network reconstruction

2014

1 Sven Herrmann and Vincent Moulton. Computing the blocks of a quasi-median graph. In DAM, Vol. 179:129-138, 2014. Keywords: abstract network, from sequences, phylogenetic network, phylogeny, polynomial, Program QuasiDec, quasi-median network, reconstruction. Note: http://arxiv.org/abs/1206.6135.

2009

2 Sarah C. Ayling and Terence A. Brown. Novel methodology for construction and pruning of quasi-median networks. In BMCB, Vol. 9:115, 2009. Keywords: abstract network, from sequences, median network, phylogenetic network, phylogeny, quasi-median network, reconstruction. Note: http://dx.doi.org/10.1186/1471-2105-9-115.         Toggle abstract "BACKGROUND: Visualising the evolutionary history of a set of sequences is a challenge for molecular phylogenetics. One approach is to use undirected graphs, such as median networks, to visualise phylogenies where reticulate relationships such as recombination or homoplasy are displayed as cycles. Median networks contain binary representations of sequences as nodes, with edges connecting those sequences differing at one character; hypothetical ancestral nodes are invoked to generate a connected network which contains all most parsimonious trees. Quasi-median networks are a generalisation of median networks which are not restricted to binary data, although phylogenetic information contained within the multistate positions can be lost during the preprocessing of data. Where the history of a set of samples contain frequent homoplasies or recombination events quasi-median networks will have a complex topology. Graph reduction or pruning methods have been used to reduce network complexity but some of these methods are inapplicable to datasets in which recombination has occurred and others are procedurally complex and/or result in disconnected networks. RESULTS: We address the problems inherent in construction and reduction of quasi-median networks. We describe a novel method of generating quasi-median networks that uses all characters, both binary and multistate, without imposing an arbitrary ordering of the multistate partitions. We also describe a pruning mechanism which maintains at least one shortest path between observed sequences, displaying the underlying relations between all pairs of sequences while maintaining a connected graph. CONCLUSION: Application of this approach to 5S rDNA sequence data from sea beet produced a pruned network within which genetic isolation between populations by distance was evident, demonstrating the value of this approach for exploration of evolutionary relationships."

2007

3 Hans-Jürgen Bandelt and Arne Dür. Translating DNA data tables into quasi-median networks for parsimony analysis and error detection. In MPE, Vol. 42(1):256-271, 2007. Keywords: abstract network, from sequences, parsimony, phylogenetic network, phylogeny, quasi-median network, reconstruction. Note: http://dx.doi.org/10.1016/j.ympev.2006.07.013.         Toggle abstract "Every DNA data table can be turned into a quasi-median network that faithfully represents the data. We show that for (weighted) condensed data tables the associated network harbors all most parsimonious reconstructions for any tree that connects the sampled haplotypes. Structural features of this network can be computed directly from the data table. The key principle repeatedly used is that the quasi-median network is uniquely determined by the sub-tables for pairs of characters. The translation of a table into a network enhances the understanding of the properties of the data in regard to homoplasy and potential artifacts. The total number of nodes of such a network measures the complexity of the data. In particular, networks that display the results of filter analyses by which hotspot mutations are removed help to detect data idiosyncrasies and thus pinpoint sequencing problems. A pertinent example drawn from human mtDNA illustrates these points. © 2006 Elsevier Inc. All rights reserved."