Who is Who in Phylogenetic Networks

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Associated keywords

compressed-network distance-between-networks distinct-cluster-network explicit-network galled-network galled-tree level-k-phylogenetic-network nested-network normal-network phylogenetic-network phylogeny polynomial regular-network spread tree-containment tree-sibling-network tree-based-network tree-child-network unicyclic-network

Article (Journal)

1 Tetsuo Asano, Jesper Jansson, Kunihiko Sadakane, Ryuhei Uehara and Gabriel Valiente. Faster computation of the Robinson–Foulds distance between phylogenetic networks. In Information Sciences, Vol. 197:77-90, 2012. Keywords: distance between networks, explicit network, level k phylogenetic network, phylogenetic network, polynomial, spread.         Toggle abstract "The Robinson-Foulds distance, a widely used metric for comparing phylogenetic trees, has recently been generalized to phylogenetic networks. Given two phylogenetic networks N 1, N 2 with n leaf labels and at most m nodes and e edges each, the Robinson-Foulds distance measures the number of clusters of descendant leaves not shared by N 1 and N 2. The fastest known algorithm for computing the Robinson-Foulds distance between N 1 and N 2 runs in O(me) time. In this paper, we improve the time complexity to O(ne/log n) for general phylogenetic networks and O(nm/log n) for general phylogenetic networks with bounded degree (assuming the word RAM model with a word length of ⌈logn⌉ bits), and to optimal O(m) time for leaf-outerplanar networks as well as optimal O(n) time for level-1 phylogenetic networks (that is, galled-trees). We also introduce the natural concept of the minimum spread of a phylogenetic network and show how the running time of our new algorithm depends on this parameter. As an example, we prove that the minimum spread of a level-k network is at most k + 1, which implies that for one level-1 and one level-k phylogenetic network, our algorithm runs in O((k + 1)e) time. © 2012 Elsevier Inc. All rights reserved."

InProceedings

2 Tetsuo Asano, Jesper Jansson, Kunihiko Sadakane, Ryuhei Uehara and Gabriel Valiente. Faster Computation of the Robinson-Foulds Distance between Phylogenetic Networks. In CPM10, Vol. 6129:190-201 of LNCS, springer, 2010. Keywords: distance between networks, explicit network, level k phylogenetic network, phylogenetic network, polynomial, spread. Note: http://hdl.handle.net/10119/9859, slides available at http://cs.nyu.edu/parida/CPM2010/MainPage_files/18.pdf.         Toggle abstract "The Robinson-Foulds distance, which is the most widely used metric for comparing phylogenetic trees, has recently been generalized to phylogenetic networks. Given two networks N1,N2 with n leaves, m nodes, and e edges, the Robinson-Foulds distance measures the number of clusters of descendant leaves that are not shared by N1 and N2. The fastest known algorithm for computing the Robinson-Foulds distance between those networks runs in O(m(m + e)) time. In this paper, we improve the time complexity to O(n(m+ e)/ log n) for general networks and O(nm/log n) for general networks with bounded degree, and to optimal O(m + e) time for planar phylogenetic networks and boundedlevel phylogenetic networks.We also introduce the natural concept of the minimum spread of a phylogenetic network and show how the running time of our new algorithm depends on this parameter. As an example, we prove that the minimum spread of a level-k phylogenetic network is at most k + 1, which implies that for two level-k phylogenetic networks, our algorithm runs in O((k + 1)(m + e)) time. © Springer-Verlag Berlin Heidelberg 2010."

MastersThesis

3 Maxime Morgado. Propriétés structurelles et relations des classes de réseaux phylogénétiques. Master's thesis, ENS Cachan, 2015. Keywords: compressed network, distinct-cluster network, explicit network, galled network, galled tree, level k phylogenetic network, nested network, normal network, phylogenetic network, phylogeny, regular network, spread, tree containment, tree sibling network, tree-based network, tree-child network, unicyclic network.