Publications related to 'weak hierarchy' : A weak hierarchy is a set of clusters such that for any three clusters C1, C2 and C3, the intersection of the three equals the intersection of two of them.

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Philippe Gambette and
Katharina Huber. On Encodings of Phylogenetic Networks of Bounded Level. In JOMB, Vol. 65(1):157180, 2012. Keywords: characterization, explicit network, from clusters, from rooted trees, from triplets, galled tree, identifiability, level k phylogenetic network, phylogenetic network, uniqueness, weak hierarchy. Note: http://hal.archivesouvertes.fr/hal00609130/en/.
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"Phylogenetic networks have now joined phylogenetic trees in the center of phylogenetics research. Like phylogenetic trees, such networks canonically induce collections of phylogenetic trees, clusters, and triplets, respectively. Thus it is not surprising that many network approaches aim to reconstruct a phylogenetic network from such collections. Related to the wellstudied perfect phylogeny problem, the following question is of fundamental importance in this context: When does one of the above collections encode (i. e. uniquely describe) the network that induces it? For the large class of level1 (phylogenetic) networks we characterize those level1 networks for which an encoding in terms of one (or equivalently all) of the above collections exists. In addition, we show that three known distance measures for comparing phylogenetic networks are in fact metrics on the resulting subclass and give the diameter for two of them. Finally, we investigate the related concept of indistinguishability and also show that many properties enjoyed by level1 networks are not satisfied by networks of higher level. © 2011 SpringerVerlag."






Philippe Gambette. Méthodes combinatoires de reconstruction de réseaux phylogénétiques. PhD thesis, Université Montpellier 2, France, 2010. Keywords: abstract network, characterization, circular split system, explicit network, FPT, from clusters, from triplets, integer linear programming, level k phylogenetic network, NP complete, phylogenetic network, phylogeny, Program Dendroscope, pyramid, reconstruction, split network, weak hierarchy. Note: http://tel.archivesouvertes.fr/tel00608342/en/.






Stefan Grünewald,
Katharina Huber,
Vincent Moulton,
Charles Semple and
Andreas Spillner. Characterizing weak compatibility in terms of weighted quartets. In Advances in Applied Mathematics, Vol. 42(3):329341, 2009. Keywords: abstract network, characterization, from quartets, split network, weak hierarchy. Note: http://www.math.canterbury.ac.nz/~c.semple/papers/GHMSS08.pdf, slides at http://www.lirmm.fr/miep08/slides/12_02_huber.pdf.






Vladimir Makarenkov,
Dmytro Kevorkov and
Pierre Legendre. Phylogenetic Network Construction Approaches. In Applied Mycology and Biotechnology, Vol. 6:6197, 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.






FrançoisJoseph Lapointe. How to account for reticulation events in phylogenetic analysis: A review of distancebased methods. In Journal of Classification, Vol. 17:175184, 2000. Keywords: abstract network, evaluation, from distances, phylogenetic network, Program Pyramids, Program SplitsTree, Program T REX, pyramid, reconstruction, reticulogram, split network, survey, weak hierarchy. Note: http://dx.doi.org/10.1007/s003570000016.






HansJürgen Bandelt and
Andreas W. M. Dress. A canonical decomposition theory for metrics on a finite set. In Advances in Mathematics, Vol. 92(1):47105, 1992. Keywords: abstract network, circular split system, from distances, split, split decomposition, split network, weak hierarchy, weakly compatible.
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"We consider specific additive decompositions d = d1 + ... + dn of metrics, defined on a finite set X (where a metric may give distance zero to pairs of distinct points). The simplest building stones are the slit metrics, associated to splits (i.e., bipartitions) of the given set X. While an additive decomposition of a Hamming metric into split metrics is in no way unique, we achieve uniqueness by restricting ourselves to coherent decompositions, that is, decompositions d = d1 + ... + dn such that for every map f:X → R with f(x) + f(y) ≥ d(x, y) for all x, y ε{lunate} X there exist maps f1, ..., fn: X → R with f = f1 + ... + fn and fi(x) + fi(y) ≥ di(x, y) for all i = 1,..., n and all x, y ε{lunate} X. These coherent decompositions are closely related to a geometric decomposition of the injective hull of the given metric. A metric with a coherent decomposition into a (weighted) sum of split metrics will be called totally splitdecomposable. Tree metrics (and more generally, the sum of two tree metrics) are particular instances of totally splitdecomposable metrics. Our main result confirms that every metric admits a coherent decomposition into a totally splitdecomposable metric and a splitprime residue, where all the split summands and hence the decomposition can be determined in polynomial time, and that a family of splits can occur this way if and only if it does not induce on any fourpoint subset all three splits with block size two. © 1992."








HansJürgen Bandelt and
Andreas W. M. Dress. Weak hierarchies associated with similarity measures: an additive clustering technique. In BMB, Vol. 51:113166, 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.
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"A new and apparently rather useful and natural concept in cluster analysis is studied: given a similarity measure on a set of objects, a subset is regarded as a cluster if any two objects a, b inside this subset 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, twodendrogram 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."



