Who is Who in Phylogenetic Networks

Publications related to 'Program WeakHierarchies' : This C++ program computes weak hierarchies from a dissimilarity matrix (available at http://www.info2.uqam.ca/~makarenv/software/Weak_Hierarchies.cpp).   Order by:   Type | Year

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Associated keywords

abstract-network clustering from-distances from-trees hybridization lateral-gene-transfer median-network NeighborNet netting phylogenetic-network phylogeny Program-Arlequin Program-Network Program-Pyramids Program-Reticlad Program-SplitsTree Program-T-REX Program-TCS Program-WeakHierarchies pyramid reconstruction reticulogram split split-decomposition split-network survey weak-hierarchy

2006

1 Vladimir Makarenkov, Dmytro Kevorkov and Pierre Legendre. Phylogenetic Network Construction Approaches. In Applied Mycology and Biotechnology, Vol. 6:61-97, 2006. Keywords: from distances, hybridization, lateral gene transfer, median network, NeighborNet, netting, Program Arlequin, Program Network, Program Pyramids, Program Reticlad, Program SplitsTree, Program T REX, Program TCS, Program WeakHierarchies, pyramid, reticulogram, split, split decomposition, split network, survey, weak hierarchy. Note: http://www.labunix.uqam.ca/~makarenv/makarenv/MKL_article.pdf.

1989

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."