Who is Who in Phylogenetic Networks

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Associated keywords

abstract-network circular-split-system clustering consensus distance-between-networks duplication explicit-network FPT from-distances from-multilabeled-tree from-network from-rooted-trees from-sequences from-splits from-trees galled-network likelihood normal-network phylogenetic-network phylogeny polynomial Program-PADRE Program-PhyloNetworks-SNaQ Program-PIRN Program-SplitsTree Program-WeakHierarchies reconstruction software split split-network SPR-distance visualization weak-hierarchy

Article (Journal)

1 Hans-Jürgen Bandelt. Combination of data in phylogenetic analysis. In PSE, Vol. Supp. 9:336-361, 1995. Keywords: from trees, phylogenetic network, phylogeny, reconstruction.         2 Hans-Jürgen Bandelt and Andreas W. M. Dress. Weak hierarchies associated with similarity measures: an additive clustering technique. In BMB, Vol. 51:113-166, 1989. Keywords: abstract network, clustering, from distances, from trees, phylogenetic network, phylogeny, Program WeakHierarchies, reconstruction, weak hierarchy. Note: http://dx.doi.org/10.1007/BF02458841.         Toggle abstract "A new and apparently rather useful and natural concept in cluster analysis is studied: given a similarity measure on a set of objects, a sub-set is regarded as a cluster if any two objects a, b inside this sub-set have greater similarity than any third object outside has to at least one of a, b. These clusters then form a closure system which can be described as a hypergraph without triangles. Conversely, given such a system, one may attach some weight to each cluster and then compose a similarity measure additively, by letting the similarity of a pair be the sum of weights of the clusters containing that particular pair. The original clusters can be reconstructed from the obtained similarity measure. This clustering model is thus located between the general additive clustering model of Shepard and Arabie (1979) and the standard hierarchical model. Potential applications include fitting dendrograms with few additional nonnested clusters and simultaneous representation of some families of multiple dendrograms (in particular, two-dendrogram solutions), as well as assisting the search for phylogenetic relationships by proposing a somewhat larger system of possibly relevant "family groups", from which an appropriate choice (based on additional insight or individual preferences) remains to be made. © 1989 Society for Mathematical Biology." 3 Andreas W. M. Dress and Daniel H. Huson. Constructing splits graphs. In TCBB, Vol. 1(3):109-115, 2004. Keywords: abstract network, circular split system, from trees, phylogenetic network, phylogeny, Program SplitsTree, reconstruction, split network, visualization. Note: http://scilib.kiev.ua/ieee/tcbb/2004/03/n3/n0109.pdf.         Toggle abstract "Phylogenetic trees correspond one-to-one to compatible systems of splits and so splits play an important role in theoretical and computational aspects of phylogeny. Whereas any tree reconstruction method can be thought of as producing a compatible system of splits, an increasing number of phylogenetlc algorithms are available that compute split systems that are not necessarily compatible and, thus, cannot always be represented by a tree. Such methods include the split decomposition, Neighbor-Net, consensus networks, and the Z-closure method. A more general split system of this kind can be represented graphically by a so-called splits graph, which generalizes the concept of a phylogenetic tree. This paper addresses the problem of computing a splits graph for a given set of splits. We have implemented all presented algorithms in a new program called SplitsTree4. © 2004 IEEE." 4 Barbara R. Holland, Katharina Huber, Vincent Moulton and Peter J. Lockhart. Using consensus networks to visualize contradictory evidence for species phylogeny. In MBE, Vol. 21(7):1459-1461, 2004. Keywords: consensus, from trees, phylogenetic network, phylogeny, split, visualization. Note: http://dx.doi.org/10.1093/molbev/msh145.         Toggle abstract Building species phylogenies from genome data requires the evaluation of phylogenetic evidence from independent gene loci. We propose an approach to do this using consensus networks. We compare gene trees for eight yeast genomes and show that consensus networks have potential for helping to visualize contradictory evidence for species phylogenies. 5 Katharina Huber, Bengt Oxelman, Martin Lott and Vincent Moulton. Reconstructing the Evolutionary History of Polyploids from Multilabeled Trees. In MBE, Vol. 23(9):1784-1791, 2007. Keywords: duplication, explicit network, from multilabeled tree, from trees, phylogenetic network, phylogeny, Program PADRE, reconstruction, software. Note: http://mbe.oxfordjournals.org/cgi/content/full/23/9/1784.         Toggle abstract "In recent studies, phylogenetic networks have been derived from so-called multilabeled trees in order to understand the origins of certain polyploids. Although the trees used in these studies were constructed using sophisticated techniques in phylogenetic analysis, the presented networks were inferred using ad hoc arguments that cannot be easily extended to larger, more complicated examples. In this paper, we present a general method for constructing such networks, which takes as input a multilabeled phylogenetic tree and outputs a phylogenetic network with certain desirable properties. To illustrate the applicability of our method, we discuss its use in reconstructing the evolutionary history of plant allopolyploids. We conclude with a discussion concerning possible future directions. The network construction method has been implemented and is freely available for use from http://www.uea.ac.uk/ ∼a043878/padre.html. © The Author 2006. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved." 6 Claudia Solís-Lemus, Paul Bastide and Cécile Ané. PhyloNetworks: A Package for Phylogenetic Networks. In MBE, Vol. 34(12):3292-3298, 2017. Keywords: from sequences, from trees, likelihood, phylogenetic network, phylogeny, Program PhyloNetworks SNaQ, reconstruction, software. Note: https://doi.org/10.1093/molbev/msx235.

InProceedings

7 Daniel H. Huson and Tobias Kloepper. Beyond Galled Trees - Decomposition and Computation of Galled Networks. In RECOMB07, Vol. 4453:211-225 of LNCS, springer, 2007. Keywords: FPT, from splits, from trees, galled network, phylogenetic network, phylogeny, Program SplitsTree, reconstruction. Note: http://dx.doi.org/10.1007/978-3-540-71681-5_15, errata..         8 Vladimir Ulyantsev and Mikhail Melnik. Constructing Parsimonious Hybridization Networks from Multiple Phylogenetic Trees Using a SAT-solver. In AlCoB15, Vol. 9199:141-153 of LNCS, springer, 2015. Keywords: explicit network, from rooted trees, from trees, phylogenetic network, phylogeny, Program PIRN, reconstruction. Note: https://www.researchgate.net/profile/Vladimir_Ulyantsev/publication/282816862_Constructing_Parsimonious_Hybridization_Networks_from_Multiple_Phylogenetic_Trees_Using_a_SAT-Solver/links/561d372c08aecade1acb3699/Constructing-Parsimonious-Hybridization-Networks-from-Multiple-Phylogenetic-Trees-Using-a-SAT-Solver.pdf.

PhdThesis

9 Devin Robert Bickner. On normal networks. PhD thesis, Iowa State University, U.S.A., 2012. Keywords: distance between networks, explicit network, from network, from trees, normal network, phylogenetic network, phylogeny, polynomial, reconstruction, SPR distance. Note: http://gradworks.umi.com/3511361.pdf.