Who is Who in Phylogenetic Networks

Search results for ' Theory and Practice of Logic Programming ' :

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1 Esra Erdem, Vladimir Lifschitz and Don Ringe. Temporal phylogenetic networks and logic programming. In Theory and Practice of Logic Programming, Vol. 6:539-558, 2006.   Note: http://arxiv.org/abs/cs/0508129v1.

2 Sha Zhu and James H. Degnan. Displayed Trees Do Not Determine Distinguishability Under the Network Multispecies Coalescent. In SB, Vol. 66(2):283-298, 2017.   Keywords: branch length, coalescent, explicit network, from network, likelihood, phylogenetic network, phylogeny, Program Hybrid-coal, Program Hybrid-Lambda, Program PhyloNet, software, uniqueness. Note: presentation available at https://www.youtube.com/watch?v=JLYGTfEZG7g.         3 Mareike Fischer, Leo van Iersel, Steven Kelk and Celine Scornavacca. On Computing The Maximum Parsimony Score Of A Phylogenetic Network. In SIDMA, Vol. 29(1):559-585, 2015.   Keywords: APX hard, cluster containment, explicit network, FPT, from network, from sequences, integer linear programming, level k phylogenetic network, NP complete, parsimony, phylogenetic network, phylogeny, polynomial, Program MPNet, reconstruction, software. Note: http://arxiv.org/abs/1302.2430.         4 Dan Gusfield. Persistent Phylogeny: A Galled-Tree and Integer Linear Programming Approach. In BCB15, Pages 443-451, 2015.   Keywords: explicit network, from binary characters, galled tree, integer linear programming, phylogenetic network, phylogeny, reconstruction. Note: http://arxiv.org/abs/1506.00678.         5 Jittat Fakcharoenphol, Tanee Kumpijit and Attakorn Putwattana. A Faster Algorithm for the Tree Containment Problem for Binary Nearly Stable Phylogenetic Networks. In Proceedings of the The 12th International Joint Conference on Computer Science and Software Engineering (JCSSE'15), Pages 337-342, IEEE, 2015.   Keywords: dynamic programming, explicit network, from network, from rooted trees, nearly-stable network, phylogenetic network, phylogeny, polynomial, tree containment.         6 Anthony Labarre and Sicco Verwer. Merging partially labelled trees: hardness and a declarative programming solution. In TCBB, Vol. 11(2):389-397, 2014.   Keywords: abstract network, from unrooted trees, heuristic, NP complete, phylogenetic network, phylogeny, reconstruction. Note: https://hal-upec-upem.archives-ouvertes.fr/hal-00855669.         Toggle abstract "Intraspecific studies often make use of haplotype networks instead of gene genealogies to represent the evolution of a set of genes. Cassens et al. proposed one such network reconstruction method, based on the global maximum parsimony principle, which was later recast by the first author of the present work as the problem of finding a minimum common supergraph of a set of t partially labelled trees. Although algorithms have been proposed for solving that problem on two graphs, the complexity of the general problem on trees remains unknown. In this paper, we show that the corresponding decision problem is NP-complete for t=3. We then propose a declarative programming approach to solving the problem to optimality in practice, as well as a heuristic approach, both based on the idpsystem, and assess the performance of both methods on randomly generated data. © 2004-2012 IEEE." 7 Lavanya Kannan and Ward C Wheeler. Exactly Computing the Parsimony Scores on Phylogenetic Networks Using Dynamic Programming. In JCB, Vol. 21(4):303-319, 2014.   Keywords: explicit network, exponential algorithm, from network, from sequences, parsimony, phylogenetic network, phylogeny, reconstruction.         Toggle abstract "Scoring a given phylogenetic network is the first step that is required in searching for the best evolutionary framework for a given dataset. Using the principle of maximum parsimony, we can score phylogenetic networks based on the minimum number of state changes across a subset of edges of the network for each character that are required for a given set of characters to realize the input states at the leaves of the networks. Two such subsets of edges of networks are interesting in light of studying evolutionary histories of datasets: (i) the set of all edges of the network, and (ii) the set of all edges of a spanning tree that minimizes the score. The problems of finding the parsimony scores under these two criteria define slightly different mathematical problems that are both NP-hard. In this article, we show that both problems, with scores generalized to adding substitution costs between states on the endpoints of the edges, can be solved exactly using dynamic programming. We show that our algorithms require O(mpk) storage at each vertex (per character), where k is the number of states the character can take, p is the number of reticulate vertices in the network, m = k for the problem with edge set (i), and m = 2 for the problem with edge set (ii). This establishes an O(nmpk2) algorithm for both the problems (n is the number of leaves in the network), which are extensions of Sankoff's algorithm for finding the parsimony scores for phylogenetic trees. We will discuss improvements in the complexities and show that for phylogenetic networks whose underlying undirected graphs have disjoint cycles, the storage at each vertex can be reduced to O(mk), thus making the algorithm polynomial for this class of networks. We will present some properties of the two approaches and guidance on choosing between the criteria, as well as traverse through the network space using either of the definitions. We show that our methodology provides an effective means to study a wide variety of datasets. © Copyright 2014, Mary Ann Liebert, Inc. 2014." 8 Julia Matsieva. A Static Formulation of the History Bound Problem. Master's thesis, UC Davis, 2014.   Keywords: bound, dynamic programming, explicit network, from binary characters, from clusters, phylogenetic network, phylogeny, polynomial. Note: https://escholarship.org/uc/item/3741t064.         9 Leo van Iersel, Celine Scornavacca and Steven Kelk. Exact reconciliation of undated trees. 2014.   Keywords: duplication, explicit network, integer linear programming, loss, phylogenetic network, phylogeny, Program ILPEACE, reconstruction. Note: https://arxiv.org/abs/1410.7004.         10 Jeremy G. Sumner, Barbara R. Holland and Peter D. Jarvis. The algebra of the general Markov model on phylogenetic trees and networks. In BMB, Vol. 74(4):858-880, 2012.   Keywords: abstract network, phylogenetic network, phylogeny, split, split network, statistical model. Note: http://arxiv.org/abs/1012.5165.         Toggle abstract "It is known that the Kimura 3ST model of sequence evolution on phylogenetic trees can be extended quite naturally to arbitrary split systems. However, this extension relies heavily on mathematical peculiarities of the associated Hadamard transformation, and providing an analogous augmentation of the general Markov model has thus far been elusive. In this paper, we rectify this shortcoming by showing how to extend the general Markov model on trees to include incompatible edges; and even further to more general network models. This is achieved by exploring the algebra of the generators of the continuous-time Markov chain together with the "splitting" operator that generates the branching process on phylogenetic trees. For simplicity, we proceed by discussing the two state case and then show that our results are easily extended to more states with little complication. Intriguingly, upon restriction of the two state general Markov model to the parameter space of the binary symmetric model, our extension is indistinguishable from the Hadamard approach only on trees; as soon as any incompatible splits are introduced the two approaches give rise to differing probability distributions with disparate structure. Through exploration of a simple example, we give an argument that our extension to more general networks has desirable properties that the previous approaches do not share. In particular, our construction allows for convergent evolution of previously divergent lineages; a property that is of significant interest for biological applications. © 2011 Society for Mathematical Biology." 11 Lavanya Kannan and Ward C Wheeler. Maximum Parsimony on Phylogenetic Networks. In ALMOB, Vol. 7:9, 2012.   Keywords: dynamic programming, explicit network, from sequences, heuristic, parsimony, phylogenetic network, phylogeny. Note: http://dx.doi.org/10.1186/1748-7188-7-9.         Toggle abstract "Background: Phylogenetic networks are generalizations of phylogenetic trees, that are used to model evolutionary events in various contexts. Several different methods and criteria have been introduced for reconstructing phylogenetic trees. Maximum Parsimony is a character-based approach that infers a phylogenetic tree by minimizing the total number of evolutionary steps required to explain a given set of data assigned on the leaves. Exact solutions for optimizing parsimony scores on phylogenetic trees have been introduced in the past.Results: In this paper, we define the parsimony score on networks as the sum of the substitution costs along all the edges of the network; and show that certain well-known algorithms that calculate the optimum parsimony score on trees, such as Sankoff and Fitch algorithms extend naturally for networks, barring conflicting assignments at the reticulate vertices. We provide heuristics for finding the optimum parsimony scores on networks. Our algorithms can be applied for any cost matrix that may contain unequal substitution costs of transforming between different characters along different edges of the network. We analyzed this for experimental data on 10 leaves or fewer with at most 2 reticulations and found that for almost all networks, the bounds returned by the heuristics matched with the exhaustively determined optimum parsimony scores.Conclusion: The parsimony score we define here does not directly reflect the cost of the best tree in the network that displays the evolution of the character. However, when searching for the most parsimonious network that describes a collection of characters, it becomes necessary to add additional cost considerations to prefer simpler structures, such as trees over networks. The parsimony score on a network that we describe here takes into account the substitution costs along the additional edges incident on each reticulate vertex, in addition to the substitution costs along the other edges which are common to all the branching patterns introduced by the reticulate vertices. Thus the score contains an in-built cost for the number of reticulate vertices in the network, and would provide a criterion that is comparable among all networks. Although the problem of finding the parsimony score on the network is believed to be computationally hard to solve, heuristics such as the ones described here would be beneficial in our efforts to find a most parsimonious network. © 2012 Kannan and Wheeler; licensee BioMed Central Ltd." 12 Jean-Philippe Doyon, Celine Scornavacca, Konstantin Yu Gorbunov, Gergely J. Szöllösi, Vincent Ranwez and Vincent Berry. An efficient algorithm for gene/species trees parsimonious reconciliation with losses, duplications, and transfers. In Proceedings of the Eighth RECOMB Comparative Genomics Satellite Workshop (RECOMB-CG'10), Vol. 6398:93-108 of LNCS, springer, 2011.   Keywords: branch length, duplication, dynamic programming, explicit network, from multilabeled tree, from species tree, from unrooted trees, lateral gene transfer, loss, phylogenetic network, phylogeny, polynomial, Program Mowgli, reconstruction. Note: http://www.lirmm.fr/~vberry/Publis/MPR-DoyonEtAl.pdf, software available at http://www.atgc-montpellier.fr/MPR/.         Toggle abstract "Tree reconciliation methods aim at estimating the evolutionary events that cause discrepancy between gene trees and species trees. We provide a discrete computational model that considers duplications, transfers and losses of genes. The model yields a fast and exact algorithm to infer time consistent and most parsimonious reconciliations. Then we study the conditions under which parsimony is able to accurately infer such events. Overall, it performs well even under realistic rates, transfers being in general less accurately recovered than duplications. An implementation is freely available at http://www.atgc- montpellier.fr/MPR. © 2010 Springer-Verlag." 13 Louxin Zhang, Yen Kaow Ng, Taoyang Wu and Yu Zheng. Network model and efficient method for detecting relative duplications or horizontal gene transfers. In ICCABS11, Pages 214-219, 2011.   Keywords: dynamic programming, explicit network, from network, from rooted trees, from species tree, phylogenetic network, phylogeny, polynomial, reconstruction.         Toggle abstract "Background: Horizontal gene transfer and gene duplication are two significant forces behind genome evolution. As more and more well-supported examples of HGTs are being revealed, there is a growing awareness that HGT is more widespread than previously thought, occurring often not only within bacteria, but also between species remotely related such as bacteria and plants or plants and animals. Although a substantial number of genomic sequences are known, HGT inference remains challenging. Parsimony-based inferences of HGT events are typically NP-hard under the framework of gene tree and species tree comparison; it is even more timeconsuming if the maximum likelihood approach is used. The fact that gene tree and species tree incongruence can be further confounded by gene duplication and gene loss events motivates us to incorporate considerations for these events into our inference of HGT events. Similarly, it will be beneficial if known HGT events are considered in the inference of gene duplications and gene losses. © 2011 IEEE." 14 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.archives-ouvertes.fr/tel-00608342/en/.         15 Yufeng Wu and Jiayin Wang. Fast Computation of the Exact Hybridization Number of Two Phylogenetic Trees. In ISBRA10, Vol. 6053:203-214 of LNCS, springer, 2010.   Keywords: agreement forest, explicit network, from rooted trees, hybridization, integer linear programming, minimum number, phylogenetic network, phylogeny, Program HybridNumber, Program SPRDist, SPR distance. Note: http://www.engr.uconn.edu/~ywu/Papers/ISBRA10WuWang.pdf.         Toggle abstract "Hybridization is a reticulate evolutionary process. An established problem on hybridization is computing the minimum number of hybridization events, called the hybridization number, needed in the evolutionary history of two phylogenetic trees. This problem is known to be NP-hard. In this paper, we present a new practical method to compute the exact hybridization number. Our approach is based on an integer linear programming formulation. Simulation results on biological and simulated datasets show that our method (as implemented in program SPRDist) is more efficient and robust than an existing method. © 2010 Springer-Verlag Berlin Heidelberg." 16 Chris Whidden, Robert G. Beiko and Norbert Zeh. Fast FPT Algorithms for Computing Rooted Agreement Forests: Theory and Experiments. In Proceedings of the ninth International Symposium on Experimental Algorithms (SEA'10), Vol. 6049:141-153 of LNCS, springer, 2010.   Keywords: agreement forest, explicit network, FPT, from rooted trees, hybridization, minimum number, phylogenetic network, phylogeny, Program HybridInterleave, reconstruction, SPR distance. Note: https://www.cs.dal.ca/sites/default/files/technical_reports/CS-2010-03.pdf.         Toggle abstract "We improve on earlier FPT algorithms for computing a rooted maximum agreement forest (MAF) or a maximum acyclic agreement forest (MAAF) of a pair of phylogenetic trees. Their sizes give the subtree-prune-and-regraft (SPR) distance and the hybridization number of the trees, respectively. We introduce new branching rules that reduce the running time of the algorithms from O(3 kn) and O(3 kn log n) to O(2.42 kn) and O(2.42 kn log n), respectively. In practice, the speed up may be much more than predicted by the worst-case analysis.We confirm this intuition experimentally by computing MAFs for simulated trees and trees inferred from protein sequence data. We show that our algorithm is orders of magnitude faster and can handle much larger trees and SPR distances than the best previous methods, treeSAT and sprdist. © Springer-Verlag Berlin Heidelberg 2010." 17 Luay Nakhleh, Derek Ruths and Hideki Innan. Gene Trees, Species Trees, and Species Networks. In R. Guerra, D. B. Allison and D. Goldstein editors, Meta-analysis and Combining Information in Genetics and Genomics, 2009.   Keywords: coalescent, explicit network, from rooted trees, from species tree, phylogenetic network, phylogeny, reconstruction. Note: http://www.cs.rice.edu/~nakhleh/Papers/GuerraGoldsteinBookChapter.pdf.         18 Philippe Gambette, Vincent Berry and Christophe Paul. The structure of level-k phylogenetic networks. In CPM09, Vol. 5577:289-300 of LNCS, springer, 2009.   Keywords: coalescent, explicit network, galled tree, level k phylogenetic network, phylogenetic network, Program Recodon. Note: http://hal-lirmm.ccsd.cnrs.fr/lirmm-00371485/en/.         Toggle abstract "Evolution is usually described as a phylogenetic tree, but due to some exchange of genetic material, it can be represented as a phylogenetic network which has an underlying tree structure. The notion of level was recently introduced as a parameter on realistic kinds of phylogenetic networks to express their complexity and tree-likeness. We study the structure of level-k networks, and how they can be decomposed into level-k generators. We also provide a polynomial time algorithm which takes as input the set of level-k generators and builds the set of level-(k + 1) generators. Finally, with a simulation study, we evaluate the proportion of level-k phylogenetic networks among networks generated according to the coalescent model with recombination. © 2009 Springer Berlin Heidelberg." 19 Laura S. Kubatko. Identifying Hybridization Events in the Presence of Coalescence via Model Selection. In Systematic Biology, Vol. 58(5):478-488, 2009.   Keywords: AIC, BIC, branch length, coalescent, explicit network, from rooted trees, from species tree, hybridization, lineage sorting, model selection, phylogenetic network, phylogeny, statistical model. Note: http://dx.doi.org/10.1093/sysbio/syp055.         20 Bui Quang Minh, Fabio Pardi, Steffen Klaere and Arndt von Haeseler. Budgeted Phylogenetic Diversity on Circular Split Systems. In TCBB, Vol. 6(1):22-29, 2009.   Keywords: abstract network, circular split system, dynamic programming, from network, phylogenetic network, polynomial, split, split network. Note: http://dx.doi.org/10.1109/TCBB.2008.54.         Toggle abstract "In the last 15 years, Phylogenetic Diversity (PD) has gained interest in the community of conservation biologists as a surrogate measure for assessing biodiversity. We have recently proposed two approaches to select taxa for maximizing PD, namely PD with budget constraints and PD on split systems. In this paper, we will unify these two strategies and present a dynamic programming algorithm to solve the unified framework of selecting taxa with maximal PD under budget constraints on circular split systems. An improved algorithm will also be given if the underlying split system is a tree. © 2006 IEEE." 21 Miguel Arenas, Gabriel Valiente and David Posada. Characterization of reticulate networks based on the coalescent with recombination. In MBE, Vol. 25(12):2517-2520, 2008.   Keywords: coalescent, evaluation, explicit network, galled tree, phylogenetic network, phylogeny, Program Recodon, regular network, simulation, tree child network, tree sibling network. Note: http://dx.doi.org/10.1093/molbev/msn219.         Toggle abstract "Phylogenetic networks aim to represent the evolutionary history of taxa. Within these, reticulate networks are explicitly able to accommodate evolutionary events like recombination, hybridization, or lateral gene transfer. Although several metrics exist to compare phylogenetic networks, they make several assumptions regarding the nature of the networks that are not likely to be fulfilled by the evolutionary process. In order to characterize the potential disagreement between the algorithms and the biology, we have used the coalescent with recombination to build the type of networks produced by reticulate evolution and classified them as regular, tree sibling, tree child, or galled trees. We show that, as expected, the complexity of these reticulate networks is a function of the population recombination rate. At small recombination rates, most of the networks produced are already more complex than regular or tree sibling networks, whereas with moderate and large recombination rates, no network fit into any of the standard classes. We conclude that new metrics still need to be devised in order to properly compare two phylogenetic networks that have arisen from reticulating evolutionary process. © 2008 The Authors." 22 Dan Gusfield, Vikas Bansal, Vineet Bafna and Yun S. Song. A Decomposition Theory for Phylogenetic Networks and Incompatible Characters. In JCB, Vol. 14(10):1247-1272, 2007.   Keywords: explicit network, from sequences, galled tree, phylogenetic network, phylogeny, Program Beagle, Program GalledTree, recombination, reconstruction, software. Note: http://www.eecs.berkeley.edu/~yss/Pub/decomposition.pdf.         23 Jesper Jansson and Wing-Kin Sung. Inferring a level-1 phylogenetic network from a dense set of rooted triplets. In TCS, Vol. 363(1):60-68, 2006. 1 comment   Keywords: explicit network, from triplets, galled tree, level k phylogenetic network, phylogenetic network, phylogeny, polynomial, reconstruction. Note: http://www.df.lth.se/~jj/Publications/ipnrt8_TCS2006.pdf.         Toggle abstract "We consider the following problem: Given a set T of rooted triplets with leaf set L, determine whether there exists a phylogenetic network consistent with T, and if so, construct one. We show that if no restrictions are placed on the hybrid nodes in the solution, the problem is trivially solved in polynomial time by a simple sorting network-based construction. For the more interesting (and biologically more motivated) case where the solution is required to be a level-1 phylogenetic network, we present an algorithm solving the problem in O (| T |2) time when T is dense, i.e., when T contains at least one rooted triplet for each cardinality three subset of L. We also give an O (| T |5 / 3)-time algorithm for finding the set of all phylogenetic networks having a single hybrid node attached to exactly one leaf (and having no other hybrid nodes) that are consistent with a given dense set of rooted triplets. © 2006 Elsevier B.V. All rights reserved." 24 Dan Gusfield and Vikas Bansal. A Fundamental Decomposition Theory for Phylogenetic Networks and Incompatible Characters. In RECOMB05, Vol. 3500:217-232 of LNCS, springer, 2005.   Keywords: explicit network, from sequences, phylogenetic network, phylogeny, polynomial, recombination, reconstruction. Note: http://wwwcsif.cs.ucdavis.edu/~gusfield/gusfieldrecomb.pdf.         25 Luay Nakhleh, Tandy Warnow, C. Randal Linder and Katherine St. John. Reconstructing reticulate evolution in species - theory and practice. In JCB, Vol. 12(6):796-811, 2005.   Keywords: from rooted trees, galled tree, phylogenetic network, phylogeny, polynomial, Program SPNet, reconstruction, software. Note: http://www.cs.rice.edu/~nakhleh/Papers/NWLSjcb.pdf.         26 Charles Choy, Jesper Jansson, Kunihiko Sadakane and Wing-Kin Sung. Computing the maximum agreement of phylogenetic networks. In Proceedings of Computing: the Tenth Australasian Theory Symposium (CATS'04), Vol. 91:134-147 of Electronic Notes in Theoretical Computer Science, 2004.   Keywords: dynamic programming, FPT, level k phylogenetic network, MASN, NP complete, phylogenetic network, phylogeny. Note: http://www.df.lth.se/~jj/Publications/masn6_CATS2004.pdf.         Toggle abstract "We introduce the maximum agreement phylogenetic subnetwork problem (MASN) of finding a branching structure shared by a set of phylogenetic networks. We prove that the problem is NP-hard even if restricted to three phylogenetic networks and give an O(n2)-time algorithm for the special case of two level-1 phylogenetic networks, where n is the number of leaves in the input networks and where N is called a level-f phylogenetic network if every biconnected component in the underlying undirected graph contains at most f nodes having indegree 2 in N. Our algorithm can be extended to yield a polynomial-time algorithm for two level-f phylogenetic networks N 1,N2 for any f which is upper-bounded by a constant; more precisely, its running time is O(|V(N1)|·|V(N 2)|·4f), where V(Ni) denotes the set of nodes of Ni. © 2004 Published by Elsevier B.V." 27 Jesper Jansson and Wing-Kin Sung. Inferring a level-1 phylogenetic network from a dense set of rooted triplets. In COCOON04, Vol. 3106:462-471 of LNCS, springer, 2004. 1 comment   Keywords: explicit network, from triplets, galled tree, level k phylogenetic network, phylogenetic network, phylogeny, polynomial, reconstruction. Note: http://www.df.lth.se/~jj/Publications/ipnrt6_COCOON2004.pdf.         28 Luay Nakhleh, Tandy Warnow and C. Randal Linder. Reconstructing reticulate evolution in species - theory and practice. In RECOMB04, Pages 337-346, 2004.   Keywords: from rooted trees, galled tree, phylogenetic network, phylogeny, polynomial, Program SPNet, reconstruction, software. Note: http://www.cs.rice.edu/~nakhleh/Papers/144-nakhleh.pdf.         29 Hans-Jürgen Bandelt and Andreas W. M. Dress. A canonical decomposition theory for metrics on a finite set. In Advances in Mathematics, Vol. 92(1):47-105, 1992.   Keywords: abstract network, circular split system, from distances, split, split decomposition, split network, weak hierarchy, weakly compatible.         Toggle abstract "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 split-decomposable. Tree metrics (and more generally, the sum of two tree metrics) are particular instances of totally split-decomposable metrics. Our main result confirms that every metric admits a coherent decomposition into a totally split-decomposable metric and a split-prime 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 four-point subset all three splits with block size two. © 1992."

30 Andrew R. Francis, Charles Semple and Mike Steel. New characterisations of tree-based networks and proximity measures. In Advances in Applied Mathematics, Vol. 93:93-107, 2018.   Keywords: characterization, explicit network, phylogenetic network, phylogeny, time consistent network, tree-based network. Note: https://arxiv.org/abs/1611.04225.         31 Leo van Iersel, Mark Jones and Celine Scornavacca. Improved maximum parsimony models for phylogenetic networks. In SB, 2018.   Keywords: explicit network, from sequences, parsimony, phylogenetic network, phylogeny, reconstruction. Note: To appear.         32 Katharina Huber, Leo van Iersel, Vincent Moulton, Celine Scornavacca and Taoyang Wu. Reconstructing phylogenetic level-1 networks from nondense binet and trinet sets. In ALG, Vol. 77(1):173-200, 2017.   Keywords: explicit network, FPT, from binets, from trinets, NP complete, phylogenetic network, phylogeny, polynomial, reconstruction. Note: http://arxiv.org/abs/1411.6804.         33 Christopher Bryant, Mareike Fischer, Simone Linz and Charles Semple. On the Quirks of Maximum Parsimony and Likelihood on Phylogenetic Networks. In JTB, Vol. 417:100-108, 2017.   Keywords: explicit network, from sequences, likelihood, parsimony, phylogenetic network, phylogeny. Note: http://arxiv.org/abs/1505.06898.         34 Monika Balvociute, David Bryant and Andreas Spillner. When can splits be drawn in the plane? In SIAM Journal on Discrete Mathematics, Vol. 31(2):839-856, 2017.   Keywords: abstract network, characterization, flat, phylogenetic network, planar, split, split network. Note: http://arxiv.org/abs/1509.06104v1.         35 Leo van Iersel, Steven Kelk, Giorgios Stamoulis, Leen Stougie and Olivier Boes. On unrooted and root-uncertain variants of several well-known phylogenetic network problems. In ALG, 2017.   Keywords: explicit network, FPT, from network, from unrooted trees, NP complete, phylogenetic network, phylogeny, reconstruction, tree containment. Note: https://hal.inria.fr/hal-01599716, to appear.         36 Philippe Gambette, Katharina Huber and Guillaume Scholz. Uprooted Phylogenetic Networks. In BMB, Vol. 79(9):2022-2048, 2017.   Keywords: circular split system, explicit network, from splits, galled tree, phylogenetic network, phylogeny, polynomial, reconstruction, split network, uniqueness. Note: http://arxiv.org/abs/1511.08387.         37 Julia Matsieva, Steven Kelk, Celine Scornavacca, Chris Whidden and Dan Gusfield. A Resolution of the Static Formulation Question for the Problem of Computing the History Bound. In TCBB, Vol. 14(2):404-417, 2017.   Keywords: ARG, explicit network, from sequences, minimum number, phylogenetic network, phylogeny.         38 Andreas Gunawan, Bhaskar DasGupta and Louxin Zhang. A decomposition theorem and two algorithms for reticulation-visible networks. In Information and Computation, Vol. 252:161-175, 2017.   Keywords: cluster containment, explicit network, from clusters, from network, from rooted trees, phylogenetic network, phylogeny, polynomial, reticulation-visible network, tree containment.. Note: https://www.cs.uic.edu/~dasgupta/resume/publ/papers/Infor_Comput_IC4848_final.pdf.         39 Mathias Weller. Linear-Time Tree Containment in Phylogenetic Networks. 2017.   Keywords: explicit network, from network, from rooted trees, nearly-stable network, phylogenetic network, phylogeny, polynomial, reconstruction, reticulation-visible network, tree containment. Note: https://arxiv.org/abs/1702.06364.         40 Hussein A. Hejase, Natalie VandePol, Gregory A. Bonito and Kevin J. Liu. FastNet: Fast and accurate inference of phylogenetic networks using large-scale genomic sequence data. 2017.   Keywords: explicit network, from rooted trees, heuristic, phylogenetic network, phylogeny, Program FastNet, reconstruction. Note: http://biorxiv.org/content/early/2017/05/01/132795.         41 Gabriel Cardona and Joan Carles Pons. Reconstruction of LGT networks from tri-LGT-nets. In JOMB, 2017.   Keywords: explicit network, From tri-LGT-nets, LGT network, phylogenetic network, phylogeny, reconstruction, uniqueness. Note: to appear.         42 Bingxin Lu, Louxin Zhang and Hon Wai Leong. A program to compute the soft Robinson-Foulds distance between phylogenetic networks. In APBC17, Vol. 18(Suppl. 2):111 of BMC Genomics, 2017.   Keywords: cluster containment, distance between networks, explicit network, exponential algorithm, from network, phylogenetic network, phylogeny, Program icelu-PhyloNetwork. Note: http://dx.doi.org/10.1186/s12864-017-3500-5.         43 Andrew R. Francis, Katharina Huber and Vincent Moulton. Tree-based unrooted phylogenetic networks. 2017.   Keywords: characterization, explicit network, NP complete, phylogenetic network, phylogeny, tree-based network. Note: https://arxiv.org/abs/1704.02062.         44 Vincent Moulton, James Oldman and Taoyang Wu. A cubic-time algorithm for computing the trinet distance between level-1 networks. In IPL, Vol. 123:36-41, 2017.   Keywords: distance between networks, explicit network, from network, phylogenetic network, phylogeny, polynomial, Program TriLoNet. Note: https://doi.org/10.1016/j.ipl.2017.03.002.         45 Magnus Bordewich, Charles Semple and Nihan Tokac. Constructing tree-child networks from distance matrices. In Algorithmica, 2017.   Keywords: compressed network, explicit network, from distances, phylogenetic network, phylogeny, polynomial, reconstruction, tree child network, uniqueness. Note: http://www.math.canterbury.ac.nz/~c.semple/papers/BSN17.pdf, to appear.         46 Celine Scornavacca, Joan Carles Pons and Gabriel Cardona. Fast algorithm for the reconciliation of gene trees and LGT networks. In JTB, Vol. 418:129-137, 2017.   Keywords: duplication, explicit network, from network, from rooted trees, lateral gene transfer, LGT network, loss, parsimony, phylogenetic network, phylogeny, polynomial, reconstruction.         47 Leo van Iersel, Vincent Moulton, Eveline De Swart and Taoyang Wu. Binets: fundamental building blocks for phylogenetic networks. In BMB, Vol. 79(5):1135-1154, 2017.   Keywords: approximation, explicit network, from binets, galled tree, level k phylogenetic network, NP complete, phylogenetic network, phylogeny, reconstruction. Note: http://dx.doi.org/10.1007/s11538-017-0275-4.         48 Juan Wang and Maozu Guo. A Metric on the Space of kth-order reduced Phylogenetic Networks. In Scientific Reports, Vol. 7(3189):1-10, 2017.   Keywords: distance between networks, explicit network, from network, kth-order reduced network, phylogenetic network, phylogeny, polynomial. Note: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5466651/.         49 Andreas Gunawan. Solving Tree Containment Problem for Reticulation-visible Networks with Optimal Running Time. 2017.   Keywords: explicit network, from network, from rooted trees, phylogenetic network, phylogeny, polynomial, reticulation-visible network, tree containment. Note: https://arxiv.org/abs/1702.04088.         50 Philippe Gambette, Andreas Gunawan, Anthony Labarre, Stéphane Vialette and Louxin Zhang. Solving the Tree Containment Problem in Linear Time for Nearly Stable Phylogenetic Networks. In DAM, 2017.   Keywords: explicit network, from network, from rooted trees, nearly-stable network, phylogenetic network, phylogeny, polynomial, tree containment. Note: https://hal-upec-upem.archives-ouvertes.fr/hal-01575001/en/, to appear.         51 Philippe Gambette, Leo van Iersel, Mark Jones, Manuel Lafond, Fabio Pardi and Celine Scornavacca. Rearrangement Moves on Rooted Phylogenetic Networks. In PLoS Computational Biology, Vol. 13(8):e1005611.1-21, 2017.   Keywords: distance between networks, explicit network, from network, NNI distance, phylogenetic network, phylogeny, SPR distance. Note: https://hal-upec-upem.archives-ouvertes.fr/hal-01572624/en/.         52 Remie Janssen, Mark Jones, Péter L. Erdös, Leo van Iersel and Celine Scornavacca. Exploring the tiers of rooted phylogenetic network space using tail moves. 2017.   Keywords: explicit network, from network, phylogenetic network, phylogeny, SPR distance. Note: https://arxiv.org/abs/1708.07656.         53 Joan Carles Pons, Charles Semple and Mike Steel. Nonbinary tree-based networks: characterisations, metrics, and support trees. 2017.   Keywords: characterization, explicit network, from network, phylogenetic network, phylogeny. Note: https://arxiv.org/abs/1710.07836.         54 Han Lai, Maureen Stolzer and Dannie Durand. Fast Heuristics for Resolving Weakly Supported Branches Using Duplication, Transfers, and Losses. In RECOMB-CG17, Vol. 10562:298-320 of LNCS, Springer, 2017.   Keywords: duplication, explicit network, from rooted trees, from species tree, lateral gene transfer, loss, phylogenetic network, phylogeny, Program Notung, reconstruction.         55 Sarah Bastkowski, Daniel Mapleson, Andreas Spillner, Taoyang Wu, Monika Balvociute and Vincent Moulton. SPECTRE: a Suite of PhylogEnetiC Tools for Reticulate Evolution. 2017.   Keywords: abstract network, NeighborNet, phylogenetic network, phylogeny, Program FlatNJ, Program QNet, Program SplitsTree, reconstruction, software, split network. Note: https://doi.org/10.1101/169177.         56 Sebastien Roch and Kun-Chieh Wang. Circular Networks from Distorted Metrics. 2017.   Keywords: abstract network, circular split system, from distances, NeighborNet, phylogenetic network, phylogeny, reconstruction, split network. Note: https://arxiv.org/abs/1707.05722.         57 Katharina Huber, Vincent Moulton, Charles Semple and Taoyang Wu. Quarnet inference rules for level-1 networks. 2017.   Keywords: explicit network, From quarnets, galled tree, level k phylogenetic network, phylogenetic network, phylogeny, reconstruction. Note: https://arxiv.org/abs/1711.06720.         58 Klaus Schliep, Alastair J. Potts, David A. Morrison and Guido W. Grimm. Intertwining phylogenetic trees and networks. In Methods in Ecology and Evolution, Vol. 8(10):1212-1220, 2017.   Keywords: abstract network, from network, from unrooted trees, phylogenetic network, phylogeny, split network, visualization. Note: http://dx.doi.org/10.1111/2041-210X.12760.         59 Timothy G. Vaughan. IcyTree: rapid browser-based visualization for phylogenetic trees and networks. In BIO, Vol. 33(15):2392-2394, 2017.   Keywords: ARG, explicit network, from network, phylogenetic network, phylogeny, Program IcyTree, software, visualization. Note: http://dx.doi.org/10.1093/bioinformatics/btx155.         60 Kristina Wicke and Mareike Fischer. Phylogenetic diversity and biodiversity indices on phylogenetic networks. 2017.   Keywords: diversity, explicit network, from network, normal network, phylogenetic network, phylogeny. Note: https://arxiv.org/abs/1706.05279.         61 Katharina Huber, Vincent Moulton and Taoyang Wu. Hierarchies from lowest stable ancestors in nonbinary phylogenetic networks. In JOC, 2017.   Keywords: characterization, explicit network, phylogenetic network, phylogeny. Note: To appear.         62 Magnus Bordewich and Charles Semple. A universal tree-based network with the minimum number of reticulations. 2017.   Keywords: explicit network, phylogenetic network, phylogeny, tree-based network. Note: https://arxiv.org/abs/1707.08274.         63 Simone Linz and Charles Semple. Attaching leaves and picking cherries to characterise the hybridisation number for a set of phylogenies. 2017.   Keywords: agreement forest, explicit network, from rooted trees, phylogenetic network, phylogeny, reconstruction, tree child network. Note: https://arxiv.org/abs/1712.04131.         64 Janosch Döcker and Simone Linz. On the existence of a cherry-picking sequence. In TCS, 2017.   Keywords: explicit network, from rooted trees, NP complete, phylogenetic network, phylogeny, reconstruction. Note: to appear.         65 Magnus Bordewich, Katharina Huber, Vincent Moulton and Charles Semple. Recovering tree-child networks from shortest inter-taxa distance information. 2017.   Keywords: explicit network, from distances, phylogenetic network, phylogeny, reconstruction, tree child network. Note: https://arxiv.org/abs/1711.08866.         66 Andrew R. Francis and Vincent Moulton. Identifiability of tree-child phylogenetic networks under a probabilistic recombination-mutation model of evolution. 2017.   Keywords: explicit network, from unrooted trees, phylogenetic network, phylogeny, tree child network, uniqueness. Note: https://arxiv.org/abs/1712.04223.         67 Leo van Iersel, Steven Kelk, Nela Lekic, Chris Whidden and Norbert Zeh. Hybridization Number on Three Rooted Binary Trees is EPT. In SIDMA, Vol. 30(3):1607-1631, 2016.   Keywords: agreement forest, explicit network, FPT, from rooted trees, hybridization, minimum number, phylogenetic network, phylogeny, reconstruction. Note: http://arxiv.org/abs/1402.2136.         68 Katharina Huber, Vincent Moulton, Mike Steel and Taoyang Wu. Folding and unfolding phylogenetic trees and networks. In JOMB, Vol. 73(6):1761-1780, 2016.   Keywords: compressed network, explicit network, FU-stable network, NP complete, phylogenetic network, phylogeny, tree containment, tree sibling network. Note: http://arxiv.org/abs/1506.04438.         69 Steven Kelk, Leo van Iersel, Celine Scornavacca and Mathias Weller. Phylogenetic incongruence through the lens of Monadic Second Order logic. In JGAA, Vol. 20(2):189-215, 2016.   Keywords: agreement forest, explicit network, FPT, from rooted trees, hybridization, minimum number, MSOL, phylogenetic network, phylogeny, reconstruction. Note: http://jgaa.info/accepted/2016/KelkIerselScornavaccaWeller2016.20.2.pdf.         70 Stephen J. Willson. Comparing and simplifying distinct-cluster phylogenetic networks. In ACOM, Vol. 20(4):917-938, 2016.   Keywords: distinct-cluster network, explicit network, phylogenetic network, phylogeny. Note: http://arxiv.org/abs/1501.07528.         71 Andreas Gunawan, Bhaskar DasGupta and Louxin Zhang. Locating a Tree in a Reticulation-Visible Network in Cubic Time. In RECOMB2016, Vol. 9649:266 of LNBI, Springer, 2016.   Keywords: cluster containment, explicit network, from clusters, from network, from rooted trees, phylogenetic network, phylogeny, polynomial, reticulation-visible network, tree containment. Note: http://arxiv.org/abs/1507.02119.         72 Sajad Mirzaei and Yufeng Wu. Fast Construction of Near Parsimonious Hybridization Networks for Multiple Phylogenetic Trees. In TCBB, Vol. 13(3):565-570, 2016.   Keywords: bound, explicit network, from rooted trees, heuristic, phylogenetic network, phylogeny, Program PIRN, reconstruction, software. Note: http://www.engr.uconn.edu/~ywu/Papers/PIRNs-preprint.pdf.         73 Philippe Gambette, Andreas Gunawan, Anthony Labarre, Stéphane Vialette and Louxin Zhang. Solving the Tree Containment Problem for Genetically Stable Networks in Quadratic Time. In IWOCA15, Vol. 9538:197-208 of LNCS, springer, 2016.   Keywords: explicit network, from network, from rooted trees, genetically stable network, phylogenetic network, phylogeny, polynomial, tree containment. Note: https://hal-upec-upem.archives-ouvertes.fr/hal-01226035 .         74 Magnus Bordewich and Charles Semple. Reticulation-visible networks. In Advances in Applied Mathematics, Vol. 78:114-141, 2016.   Keywords: explicit network, from network, from rooted trees, phylogenetic network, phylogeny, polynomial, tree containment. Note: http://www.math.canterbury.ac.nz/~c.semple/papers/BS16.pdf.         75 Louxin Zhang. On Tree-Based Phylogenetic Networks. In JCB, Vol. 23(7):553-565, 2016.   Keywords: characterization, explicit network, phylogenetic network, phylogeny, tree-based network. Note: http://arxiv.org/abs/1509.01663.         76 Vincent Ranwez, Celine Scornavacca, Jean-Philippe Doyon and Vincent Berry. Inferring gene duplications, transfers and losses can be done in a discrete framework. In JOMB, Vol. 72(7):1811-1844, 2016.   Keywords: duplication, explicit network, from rooted trees, from species tree, lateral gene transfer, loss, phylogenetic network, phylogeny, reconstruction.         77 Claudia Solís-Lemus and Cécile Ané. Inferring phylogenetic networks with maximum pseudolikelihood under incomplete lineage sorting. In PLOS Genetics, Vol. 12(3):e1005896, 2016.   Keywords: explicit network, from quartets, from unrooted trees, likelihood, phylogenetic network, phylogeny, Program PhyloNetworks SNaQ. Note: http://arxiv.org/abs/1509.06075v1.         78 François Chevenet, Jean-Philippe Doyon, Celine Scornavacca, Edwin Jacox, Emmanuelle Jousselin and Vincent Berry. SylvX: a viewer for phylogenetic tree reconciliations. In BIO, Vol. 32(4):608-610, 2016.   Keywords: duplication, explicit network, from rooted trees, from species tree, lateral gene transfer, loss, phylogenetic network, phylogeny, Program SylvX, software, visualization. Note: https://www.researchgate.net/profile/Emmanuelle_Jousselin/publication/283446016_SylvX_a_viewer_for_phylogenetic_tree_reconciliations/links/5642146108aec448fa621efa.pdf.         79 Hussein A. Hejase and Kevin J. Liu. A scalability study of phylogenetic network inference methods using empirical datasets and simulations involving a single reticulation. Vol. 17(422):1-12, 2016.   Keywords: abstract network, evaluation, from sequences, phylogenetic network, phylogeny, Program PhyloNet, Program PhyloNetworks SNaQ, reconstruction, simulation, unicyclic network. Note: http://dx.doi.org/10.1186/s12859-016-1277-1.         80 Ioannis G. Tollis and Konstantinos G. Kakoulis. Algorithms for Visualizing Phylogenetic Networks. In GD16, Vol. 9801:183-195 of LNCS, springer, 2016.   Keywords: explicit network, galled network, galled tree, NP complete, planar, visualization. Note: http://arxiv.org/abs/1609.00755.         81 Philippe Gambette, Leo van Iersel, Steven Kelk, Fabio Pardi and Celine Scornavacca. Do branch lengths help to locate a tree in a phylogenetic network? In BMB, Vol. 78(9):1773-1795, 2016.   Keywords: branch length, explicit network, FPT, from network, from rooted trees, NP complete, phylogenetic network, phylogeny, pseudo-polynomial, time consistent network, tree containment, tree sibling network. Note: http://arxiv.org/abs/1607.06285.         82 Laura Jetten and Leo van Iersel. Nonbinary tree-based phylogenetic networks. In TCBB, 2016.   Keywords: characterization, explicit network, phylogenetic network, phylogeny, tree-based network. Note: http://arxiv.org/abs/1601.04974.         83 Nikita Alexeev and Max A. Alekseyev. Combinatorial Scoring of Phylogenetic Networks. In COCOON16, Vol. 9797:560-572 of LNCS, Springer, 2016.   Keywords: cactus graph, enumeration, explicit network, galled tree, phylogenetic network, phylogeny. Note: http://arxiv.org/abs/1602.02841.         84 Charles Semple. Phylogenetic Networks with Every Embedded Phylogenetic Tree a Base Tree. In BMB, Vol. 78(1):132-137, 2016.   Keywords: characterization, explicit network, phylogenetic network, phylogeny, tree child network, tree-based network. Note: http://www.math.canterbury.ac.nz/~c.semple/papers/S15.pdf.         85 Maria Anaya, Olga Anipchenko-Ulaj, Aisha Ashfaq, Joyce Chiu, Mahedi Kaiser, Max Shoji Ohsawa, Megan Owen, Ella Pavlechko, Katherine St. John, Shivam Suleria, Keith Thompson and Corrine Yap. On Determining if Tree-based Networks Contain Fixed Trees. In BMB, Vol. 78(5):961-969, 2016.   Keywords: explicit network, FPT, NP complete, phylogenetic network, phylogeny, tree-based network. Note: http://arxiv.org/abs/1602.02739.         86 Momoko Hayamizu. On the existence of infinitely many universal tree-based networks. In JTB, Vol. 396:204-206, 2016.   Keywords: explicit network, phylogenetic network, phylogeny, tree-based network. Note: http://arxiv.org/abs/1512.02402.         87 James Oldman, Taoyang Wu, Leo van Iersel and Vincent Moulton. TriLoNet: Piecing together small networks to reconstruct reticulate evolutionary histories. In MBE, Vol. 33(8):2151-2162, 2016.   Keywords: explicit network, from trinets, galled tree, phylogenetic network, phylogeny, Program LEV1ATHAN, Program TriLoNet, reconstruction.         88 Dingqiao Wen, Yun Yu and Luay Nakhleh. Bayesian Inference of Reticulate Phylogenies under the Multispecies Network Coalescent. In PLoS Genetics, Vol. 12(5):e1006006, 2016.   Keywords: bayesian, coalescent, phylogenetic network, phylogeny, Program PhyloNet, reconstruction, software.         89 Jiafan Zhu, Yun Yu and Luay Nakhleh. In the Light of Deep Coalescence: Revisiting Trees Within Networks. In RECOMB-CG16, Vol. 17(suppl. 14):415.271-282 of BMCB, 2016.   Keywords: branch length, evaluation, explicit network, phylogenetic network, phylogeny, statistical model, tree-based network. Note: http://arxiv.org/abs/1606.07350.         90 Magnus Bordewich and Nihan Tokac. An algorithm for reconstructing ultrametric tree-child networks from inter-taxa distances. In DAM, Vol. 213:47-59, 2016.   Keywords: explicit network, from distances, phylogenetic network, phylogeny, reconstruction, tree child network. Note: http://dx.doi.org/10.1016/j.dam.2016.05.011.         91 Mike Steel. Introduction to phylogenetic networks. In Phylogeny: Discrete and Random Processes in Evolution, Vol. 89 of CBMS-NSF Regional Conference Series in Applied Mathematics, Chapter 10, SIAM, 2016.   Keywords: abstract network, explicit network, phylogenetic network, phylogeny, survey. Note: http://bookstore.siam.org/cb89/.         92 Juan Wang. A Survey of Methods for Constructing Rooted Phylogenetic Networks. In PLoS ONE, Vol. 11(11):e0165834, 2016.   Keywords: evaluation, explicit network, from clusters, phylogenetic network, phylogeny, Program BIMLR, Program Dendroscope, Program LNetwork, reconstruction, survey. Note: http://dx.doi.org/10.1371/journal.pone.0165834.         93 Nihan Tokac. Efficiency of Algorithms in Phylogenetics. PhD thesis, Durham University, U.K., 2016.   Keywords: explicit network, from distances, phylogenetic network, phylogeny, reconstruction, tree child network. Note: http://etheses.dur.ac.uk/11768/.         94 Leo van Iersel, Steven Kelk and Celine Scornavacca. Kernelizations for the hybridization number problem on multiple nonbinary trees. In JCSS, Vol. 82(6):1075-1089, 2016.   Keywords: explicit network, from rooted trees, kernelization, minimum number, phylogenetic network, phylogeny, Program Treeduce, reconstruction. Note: https://arxiv.org/abs/1311.4045v3.         95 Colin McDiarmid, Charles Semple and Dominic Welsh. Counting phylogenetic networks. In Annals of Combinatorics, Vol. 19(1):205-224, 2015.   Keywords: counting, explicit network, normal network, phylogenetic network, phylogeny, tree child network. Note: http://www.math.canterbury.ac.nz/~c.semple/papers/MSW13.pdf.         96 Katharina Huber, Leo van Iersel, Vincent Moulton and Taoyang Wu. How much information is needed to infer reticulate evolutionary histories? In Systematic Biology, Vol. 64(1):102-111, 2015.   Keywords: explicit network, from network, from rooted trees, from trinets, identifiability, phylogenetic network, phylogeny, reconstruction, uniqueness. Note: http://dx.doi.org/10.1093/sysbio/syu076.         97 Andrew R. Francis and Mike Steel. Which phylogenetic networks are merely trees with additional arcs? In Systematic Biology, Vol. 64(5):768-777, 2015.   Keywords: explicit network, phylogenetic network, phylogeny, polynomial, tree-based network. Note: http://arxiv.org/abs/1502.07045.         98 Fabio Pardi and Celine Scornavacca. Reconstructible Phylogenetic Networks: Do Not Distinguish the Indistinguishable. In PLoS Computational Biology, Vol. 11(4), 2015.   Keywords: branch length, explicit network, from rooted trees, identifiability, phylogenetic network, phylogeny, reconstruction. Note: http://dx.doi.org/10.1371/journal.pcbi.1004135.         99 Philippe Gambette, Andreas Gunawan, Anthony Labarre, Stéphane Vialette and Louxin Zhang. Locating a Tree in A Phylogenetic Network in Quadratic Time. In RECOMB15, Vol. 9029:96-107 of LNCS, Springer, 2015.   Keywords: evaluation, explicit network, from network, from rooted trees, genetically stable network, nearly-stable network, phylogenetic network, phylogeny, polynomial, tree containment. Note: https://hal.archives-ouvertes.fr/hal-01116231/en.         100 Quan Nguyen and Teemu Roos. Likelihood-based inference of phylogenetic networks from sequence data by PhyloDAG. In ALCOB15, Vol. 9199:126-140 of LNCS, springer, 2015.   Keywords: BIC, explicit network, from sequences, likelihood, phylogenetic network, phylogeny, Program PhyloDAG, reconstruction, software. Note: http://www.cs.helsinki.fi/u/ttonteri/pub/alcob2015.pdf.         101 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.         102 Yun Yu and Luay Nakhleh. A Distance-Based Method for Inferring Phylogenetic Networks in the Presence of Incomplete Lineage Sorting. In ISBRA15, Vol. 9096:378-389 of LNCS, springer, 2015.   Keywords: bootstrap, explicit network, from distances, heuristic, incomplete lineage sorting, phylogenetic network, phylogeny, reconstruction. Note: http://bioinfo.cs.rice.edu/sites/bioinfo.cs.rice.edu/files/YuNakhleh-ISBRA15.pdf.         103 Benjamin Albrecht. Computing all hybridization networks for multiple binary phylogenetic input trees. In BMCB, Vol. 16(236):1-15, 2015.   Keywords: agreement forest, explicit network, exponential algorithm, FPT, from rooted trees, phylogenetic network, phylogeny, Program Hybroscale, Program PIRN, reconstruction. Note: http://dx.doi.org/10.1186/s12859-015-0660-7.         104 Ward C Wheeler. Phylogenetic network analysis as a parsimony optimization problem. In BMCB, Vol. 16(296):1-9, 2015.   Keywords: explicit network, from sequences, parsimony, phylogenetic network, phylogeny, reconstruction. Note: http://dx.doi.org/10.1186/s12859-015-0675-0.         105 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 child network, tree containment, tree sibling network, tree-based network, unicyclic network.         106 Yun Yu and Luay Nakhleh. A maximum pseudo-likelihood approach for phylogenetic networks. In RECOMB-CG15, Vol. 16(Suppl 10)(S10):1-10 of BMC Genomics, BioMed Central, 2015.   Keywords: explicit network, from rooted trees, hybridization, incomplete lineage sorting, likelihood, phylogenetic network, phylogeny, Program PhyloNet, reconstruction, tripartition distance. Note: http://dx.doi.org/10.1186/1471-2164-16-S10-S10.         107 Sha Zhu, James H. Degnan, Sharyn J. Goldstein and Bjarki Eldon. Hybrid-Lambda: simulation of multiple merger and Kingman gene genealogies in species networks and species trees. In BMCB, Vol. 16(292):1-7, 2015.   Keywords: explicit network, from network, phylogenetic network, phylogeny, Program Hybrid-Lambda, simulation, software. Note: http://dx.doi.org/10.1186/s12859-015-0721-y.         108 Gergely J. Szöllösi, Adrián Arellano Davín, Eric Tannier, Vincent Daubin and Bastien Boussau. Genome-scale phylogenetic analysis finds extensive gene transfer among fungi. In Philosophical Transactions of the Royal Society of London B: Biological Sciences, Vol. 370(1678):1-11, 2015.   Keywords: duplication, from sequences, lateral gene transfer, loss, phylogenetic network, phylogeny, Program ALE, reconstruction. Note: http://dx.doi.org/10.1098/rstb.2014.0335.         109 Thu-Hien To and Celine Scornavacca. Efficient algorithms for reconciling gene trees and species networks via duplication and loss events. In RECOMB-CG15, Vol. 16(Suppl 10)(S6):1-14 of BMC Genomics, BioMed Central, 2015.   Keywords: explicit network, from network, from rooted trees, phylogenetic network, phylogeny, polynomial, reconstruction. Note: http://dx.doi.org/10.1186/1471-2164-16-S10-S6.         110 Dwueng-Chwuan Jhwueng and Brian O'Meara. Trait Evolution on Phylogenetic Networks. 2015.   Keywords: explicit network, from network, hybridization, phylogenetic network, phylogeny, Program BMhyd, statistical model. Note: http://dx.doi.org/10.1101/023986.         111 Andreas Gunawan and Louxin Zhang. Bounding the Size of a Network Defined By Visibility Property. 2015.   Keywords: bound, explicit network, galled network, nearly-stable network, phylogenetic network, phylogeny, reticulation-visible network, stable-child network. Note: http://arxiv.org/abs/1510.00115.         112 Marc Thuillard and Didier Fraix-Burnet. Phylogenetic Trees and Networks Reduce to Phylogenies on Binary States: Does It Furnish an Explanation to the Robustness of Phylogenetic Trees against Lateral Transfers? In Evolutionary Bioinformatics, Vol. 11:213-221, 2015. [Abstract]   Keywords: circular split system, explicit network, from multistate characters, outerplanar, perfect, phylogenetic network, phylogeny, planar, polynomial, reconstruction, split. Note: http://dx.doi.org/10.4137%2FEBO.S28158.         113 Laura Jetten. Characterising tree-based phylogenetic networks. Bachelor thesis, 2015.   Keywords: characterization, explicit network, phylogenetic network, phylogeny, tree-based network. Note: http://resolver.tudelft.nl/uuid:fda2636d-0ed5-4dd2-bacf-8abbbad8994e.         114 Benjamin Albrecht. Computing a Relevant Set of Nonbinary Maximum Acyclic Agreement Forests. 2015.   Keywords: agreement forest, explicit network, exponential algorithm, from rooted trees, phylogenetic network, phylogeny, Program Hybroscale, reconstruction, software. Note: http://arxiv.org/abs/1512.05703.         115 Benjamin Albrecht. Fast computation of all maximum acyclic agreement forests for two rooted binary phylogenetic trees. 2015.   Keywords: agreement forest, explicit network, from rooted trees, phylogenetic network, phylogeny, Program Hybroscale, reconstruction, software. Note: http://arxiv.org/abs/1512.05656.         116 Nela Lekic. Trees, agreement forests and treewidth: combinatorial algorithms for constructing phylogenetic networks. PhD thesis, Maastricht University, The Netherlands, 2015.   Keywords: explicit network, from rooted trees, phylogenetic network, phylogeny, reconstruction.         117 Jessica W. Leigh and David Bryant. PopART: full-feature software for haplotype network construction. In Methods in Ecology and Evolution, Vol. 6(9):1110-1116, 2015.   Keywords: abstract network, from sequences, haplotype network, MedianJoining, phylogenetic network, phylogeny, population genetics, Program PopART, Program TCS, software. Note: http://dx.doi.org/10.1111/2041-210X.12410.         118 Gabriel Cardona, Joan Carles Pons and Francesc Rosselló. A reconstruction problem for a class of phylogenetic networks with lateral gene transfers. In ALMOB, Vol. 10(28):1-15, 2015.   Keywords: explicit network, from rooted trees, lateral gene transfer, phylogenetic network, phylogeny, Program LGTnetwork, reconstruction, software, tree-based network. Note: http://dx.doi.org/10.1186/s13015-015-0059-z.         119 Gabriel Cardona, Mercè Llabrés, Francesc Rosselló and Gabriel Valiente. The comparison of tree-sibling time consistent phylogenetic networks is graph-isomorphism complete. In The Scientific World Journal, Vol. 2014(254279):1-6, 2014.   Keywords: abstract network, distance between networks, from network, isomorphism, phylogenetic network, tree sibling network. Note: http://arxiv.org/abs/0902.4640.         Toggle abstract "Several polynomial time computable metrics on the class of semibinary tree-sibling time consistent phylogenetic networks are available in the literature; in particular, the problem of deciding if two networks of this kind are isomorphic is in P. In this paper, we show that if we remove the semibinarity condition, then the problem becomes much harder. More precisely, we prove that the isomorphism problem for generic tree-sibling time consistent phylogenetic networks is polynomially equivalent to the graph isomorphism problem. Since the latter is believed not to belong to P, the chances are that it is impossible to define a metric on the class of all tree-sibling time consistent phylogenetic networks that can be computed in polynomial time. © 2014 Gabriel Cardona et al." 120 Steven Kelk and Celine Scornavacca. Constructing minimal phylogenetic networks from softwired clusters is fixed parameter tractable. In ALG, Vol. 68(4):886-915, 2014.   Keywords: explicit network, FPT, from clusters, level k phylogenetic network, phylogenetic network, phylogeny, reconstruction. Note: http://arxiv.org/abs/1108.3653.         Toggle abstract "Here we show that, given a set of clusters C on a set of taxa X, where |X|=n, it is possible to determine in time f(k)×poly(n) whether there exists a level-≤k network (i.e. a network where each biconnected component has reticulation number at most k) that represents all the clusters in C in the softwired sense, and if so to construct such a network. This extends a result from Kelk et al. (in IEEE/ACM Trans. Comput. Biol. Bioinform. 9:517-534, 2012) which showed that the problem is polynomial-time solvable for fixed k. By defining "k-reticulation generators" analogous to "level-k generators", we then extend this fixed parameter tractability result to the problem where k refers not to the level but to the reticulation number of the whole network. © 2012 Springer Science+Business Media New York." 121 Hadi Poormohammadi, Changiz Eslahchi and Ruzbeh Tusserkani. TripNet: A Method for Constructing Rooted Phylogenetic Networks from Rooted Triplets. In PLoS ONE, Vol. 9(9):e106531, 2014.   Keywords: explicit network, from triplets, heuristic, level k phylogenetic network, phylogenetic network, phylogeny, Program TripNet, reconstruction, software. Note: http://arxiv.org/abs/1201.3722.         Toggle abstract "The problem of constructing an optimal rooted phylogenetic network from an arbitrary set of rooted triplets is an NP-hard problem. In this paper, we present a heuristic algorithm called TripNet, which tries to construct a rooted phylogenetic network with the minimum number of reticulation nodes from an arbitrary set of rooted triplets. Despite of current methods that work for dense set of rooted triplets, a key innovation is the applicability of TripNet to non-dense set of rooted triplets. We prove some theorems to clarify the performance of the algorithm. To demonstrate the efficiency of TripNet, we compared TripNet with SIMPLISTIC. It is the only available software which has the ability to return some rooted phylogenetic network consistent with a given dense set of rooted triplets. But the results show that for complex networks with high levels, the SIMPLISTIC running time increased abruptly. However in all cases TripNet outputs an appropriate rooted phylogenetic network in an acceptable time. Also we tetsed TripNet on the Yeast data. The results show that Both TripNet and optimal networks have the same clustering and TripNet produced a level-3 network which contains only one more reticulation node than the optimal network." 122 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.         123 Leo van Iersel and Vincent Moulton. Trinets encode tree-child and level-2 phylogenetic networks. In JOMB, Vol. 68(7):1707-1729, 2014.   Keywords: explicit network, from trinets, level k phylogenetic network, phylogenetic network, phylogeny, reconstruction. Note: http://arxiv.org/abs/1210.0362.         Toggle abstract "Phylogenetic networks generalize evolutionary trees, and are commonly used to represent evolutionary histories of species that undergo reticulate evolutionary processes such as hybridization, recombination and lateral gene transfer. Recently, there has been great interest in trying to develop methods to construct rooted phylogenetic networks from triplets, that is rooted trees on three species. However, although triplets determine or encode rooted phylogenetic trees, they do not in general encode rooted phylogenetic networks, which is a potential issue for any such method. Motivated by this fact, Huber and Moulton recently introduced trinets as a natural extension of rooted triplets to networks. In particular, they showed that level-1 phylogenetic networks are encoded by their trinets, and also conjectured that all "recoverable" rooted phylogenetic networks are encoded by their trinets. Here we prove that recoverable binary level-2 networks and binary tree-child networks are also encoded by their trinets. To do this we prove two decomposition theorems based on trinets which hold for all recoverable binary rooted phylogenetic networks. Our results provide some additional evidence in support of the conjecture that trinets encode all recoverable rooted phylogenetic networks, and could also lead to new approaches to construct phylogenetic networks from trinets. © 2013 Springer-Verlag Berlin Heidelberg." 124 Judith Keijsper and Rudi Pendavingh. Reconstructing a phylogenetic level-1 network from quartets. In BMB, Vol. 76(10):2517-2541, 2014.   Keywords: explicit network, from quartets, galled tree, phylogenetic network, phylogeny, polynomial, reconstruction. Note: http://arxiv.org/abs/1308.5206.         125 Leo van Iersel and Steven Kelk. Kernelizations for the hybridization number problem on multiple nonbinary trees. In WG14, Vol. 8747:299-311 of LNCS, springer, 2014.   Keywords: explicit network, from rooted trees, kernelization, minimum number, phylogenetic network, phylogeny, Program Treeduce, reconstruction. Note: http://arxiv.org/abs/1311.4045.         126 Jesper Jansson and Andrzej Lingas. Computing the rooted triplet distance between galled trees by counting triangles. In Journal of Discrete Algorithms, Vol. 25:66-78, 2014.   Keywords: distance between networks, explicit network, from network, galled network, phylogenetic network, phylogeny, polynomial, triplet distance.         Toggle abstract "We consider a generalization of the rooted triplet distance between two phylogenetic trees to two phylogenetic networks. We show that if each of the two given phylogenetic networks is a so-called galled tree with n leaves then the rooted triplet distance can be computed in o(n2.687) time. Our upper bound is obtained by reducing the problem of computing the rooted triplet distance between two galled trees to that of counting monochromatic and almost-monochromatic triangles in an undirected, edge-colored graph. To count different types of colored triangles in a graph efficiently, we extend an existing technique based on matrix multiplication and obtain several new algorithmic results that may be of independent interest: (i) the number of triangles in a connected, undirected, uncolored graph with m edges can be computed in o(m1.408) time; (ii) if G is a connected, undirected, edge-colored graph with n vertices and C is a subset of the set of edge colors then the number of monochromatic triangles of G with colors in C can be computed in o(n2.687) time; and (iii) if G is a connected, undirected, edge-colored graph with n vertices and R is a binary relation on the colors that is computable in O(1) time then the number of R-chromatic triangles in G can be computed in o(n2.687) time. © 2013 Elsevier B.V. All rights reserved." 127 Ward C Wheeler. Phyletic groups on networks. In Cladistics, Vol. 30(4):447-451, 2014.   Keywords: explicit network, from network, phylogenetic network, phylogeny. Note: http://dx.doi.org/10.1111/cla.12062.         Toggle abstract "Three additional phyletic group types, "periphyletic," "epiphyletic", and "anaphyletic" (in addition to Hennigian mono-, para-, and polyphyletic) are defined in terms of trees and phylogenetic networks (trees with directed reticulate edges) via a generalization of the algorithmic definitions of Farris. These designations concern groups defined as monophyletic on trees, but with additional gains or losses of members from network edges. These distinctions should be useful in discussion of systems with non-vertical inheritance such as recombination between viruses, horizontal exchange between bacteria, hybridization in plants and animals, as well as human linguistic evolution. Examples are illustrated with Indo-European language groups. © The Willi Hennig Society 2013." 128 Jialiang Yang, Stefan Grünewald, Yifei Xu and Xiu-Feng Wan. Quartet-based methods to reconstruct phylogenetic networks. In BMC Systems Biology, Vol. 80(21), 2014.   Keywords: abstract network, from quartets, phylogenetic network, phylogeny, Program QuartetMethods, Program QuartetNet, Program SplitsTree, reconstruction. Note: http://dx.doi.org/10.1186/1752-0509-8-21 .         Toggle abstract "Background: Phylogenetic networks are employed to visualize evolutionary relationships among a group of nucleotide sequences, genes or species when reticulate events like hybridization, recombination, reassortant and horizontal gene transfer are believed to be involved. In comparison to traditional distance-based methods, quartet-based methods consider more information in the reconstruction process and thus have the potential to be more accurate.Results: We introduce QuartetSuite, which includes a set of new quartet-based methods, namely QuartetS, QuartetA, and QuartetM, to reconstruct phylogenetic networks from nucleotide sequences. We tested their performances and compared them with other popular methods on two simulated nucleotide sequence data sets: one generated from a tree topology and the other from a complicated evolutionary history containing three reticulate events. We further validated these methods to two real data sets: a bacterial data set consisting of seven concatenated genes of 36 bacterial species and an influenza data set related to recently emerging H7N9 low pathogenic avian influenza viruses in China.Conclusion: QuartetS, QuartetA, and QuartetM have the potential to accurately reconstruct evolutionary scenarios from simple branching trees to complicated networks containing many reticulate events. These methods could provide insights into the understanding of complicated biological evolutionary processes such as bacterial taxonomy and reassortant of influenza viruses. © 2014 Yang et al.; licensee BioMed Central Ltd." 129 Kevin J. Liu, Jingxuan Dai, Kathy Truong, Ying Song, Michael H. Kohn and Luay Nakhleh. An HMM-Based Comparative Genomic Framework for Detecting Introgression in Eukaryotes. In PLoS ONE, Vol. 10(6):e1003649, 2014.   Keywords: explicit network, from network, phylogenetic network, phylogeny, Program PhyloNet-HMM. Note: http://arxiv.org/abs/1310.7989.         Toggle abstract "One outcome of interspecific hybridization and subsequent effects of evolutionary forces is introgression, which is the integration of genetic material from one species into the genome of an individual in another species. The evolution of several groups of eukaryotic species has involved hybridization, and cases of adaptation through introgression have been already established. In this work, we report on PhyloNet-HMM-a new comparative genomic framework for detecting introgression in genomes. PhyloNet-HMM combines phylogenetic networks with hidden Markov models (HMMs) to simultaneously capture the (potentially reticulate) evolutionary history of the genomes and dependencies within genomes. A novel aspect of our work is that it also accounts for incomplete lineage sorting and dependence across loci. Application of our model to variation data from chromosome 7 in the mouse (Mus musculus domesticus) genome detected a recently reported adaptive introgression event involving the rodent poison resistance gene Vkorc1, in addition to other newly detected introgressed genomic regions. Based on our analysis, it is estimated that about 9% of all sites within chromosome 7 are of introgressive origin (these cover about 13 Mbp of chromosome 7, and over 300 genes). Further, our model detected no introgression in a negative control data set. We also found that our model accurately detected introgression and other evolutionary processes from synthetic data sets simulated under the coalescent model with recombination, isolation, and migration. Our work provides a powerful framework for systematic analysis of introgression while simultaneously accounting for dependence across sites, point mutations, recombination, and ancestral polymorphism. © 2014 Liu et al." 130 David A. Morrison. Phylogenetic Networks: A Review of Methods to Display Evolutionary History. In Annual Research & Review in Biology, Vol. 4(10):1518-1543, 2014.   Keywords: explicit network, phylogenetic network, phylogeny, reconstruction, survey.         131 David A. Morrison. Rooted Phylogenetic Networks for Exploratory Data Analysis. In Advances in Research, Vol. 2(3):145-152, 2014.   Keywords: abstract network, explicit network, phylogenetic network, reconstruction.         132 David A. Morrison. Next generation sequencing and phylogenetic networks. In EMBnet.journal, Vol. 20(e760):1-4, 2014.   Keywords: abstract network, from NGS data, phylogenetic network, phylogeny, Program SplitsTree, reconstruction.         133 Dan Gusfield. ReCombinatorics: The Algorithmics of Ancestral Recombination Graphs and Explicit Phylogenetic Networks. MIT Press, 2014.   Keywords: ARG, explicit network, phylogenetic network, phylogeny, survey. Note: http://mitpress.mit.edu/books/recombinatorics.         134 Josh Voorkamp né Collins. Untangling Evolution. PhD thesis, University of Otago, New Zealand, 2014.   Keywords: agreement forest, explicit network, from rooted trees, generation, phylogenetic network, phylogeny, reconstruction. Note: http://otago.ourarchive.ac.nz/handle/10523/4802.         135 Vladimir Makarenkov, Alix Boc and Pierre Legendre. A New Algorithm for Inferring Hybridization Events Based on the Detection of Horizontal Gene Transfers. In Fuad Aleskerov, Boris Goldengorin and Panos M. Pardalos editors, Clusters, Orders, and Trees: Methods and Applications, Vol. 92 of Springer Optimization and Its Applications, Springer, 2014.   Keywords: explicit network, phylogenetic network, phylogeny, reconstruction.         136 Leo van Iersel, Steven Kelk, Nela Lekic and Celine Scornavacca. A practical approximation algorithm for solving massive instances of hybridization number for binary and nonbinary trees. In BMCB, Vol. 15(127):1-12, 2014.   Keywords: agreement forest, approximation, explicit network, from rooted trees, phylogenetic network, phylogeny, Program CycleKiller, Program TerminusEst, reconstruction. Note: http://dx.doi.org/10.1186/1471-2105-15-127.         137 Monika Balvociute, Andreas Spillner and Vincent Moulton. FlatNJ: A Novel Network-Based Approach to Visualize Evolutionary and Biogeographical Relationships. In Systematic Biology, Vol. 63(3):383-396, 2014.   Keywords: abstract network, flat, phylogenetic network, phylogeny, Program FlatNJ, Program SplitsTree, split network. Note: http://dx.doi.org/10.1093/sysbio/syu001.         Toggle abstract "Split networks are a type of phylogenetic network that allow visualization of conflict in evolutionary data. We present a new method for constructing such networks called FlatNetJoining (FlatNJ). A key feature of FlatNJ is that it produces networks that can be drawn in the plane in which labels may appear inside of the network. For complex data sets that involve, for example, non-neutral molecular markers, this can allow additional detail to be visualized as compared to previous methods such as split decomposition and NeighborNet. We illustrate the application of FlatNJ by applying it to whole HIV genome sequences, where recombination has taken place, fluorescent proteins in corals, where ancestral sequences are present, and mitochondrial DNA sequences from gall wasps, where biogeographical relationships are of interest. We find that the networks generated by FlatNJ can facilitate the study of genetic variation in the underlying molecular sequence data and, in particular, may help to investigate processes such as intra-locus recombination. FlatNJ has been implemented in Java and is freely available at www.uea.ac.uk/computing/software/ flatnj. [flat split system; NeighborNet; Phylogenetic network; QNet; split; split network.] © The Author(s) 2014." 138 Johann-Mattis List, Shijulal Nelson-Sathi, Hans Geisler and William Martin. Networks of lexical borrowing and lateral gene transfer in language and genome evolution. In BioEssays, Vol. 36(2):141-150, 2014.   Keywords: explicit network, minimal lateral network, phylogenetic network, Program lingpy. Note: http://dx.doi.org/10.1002/bies.201300096.         Toggle abstract "Like biological species, languages change over time. As noted by Darwin, there are many parallels between language evolution and biological evolution. Insights into these parallels have also undergone change in the past 150 years. Just like genes, words change over time, and language evolution can be likened to genome evolution accordingly, but what kind of evolution? There are fundamental differences between eukaryotic and prokaryotic evolution. In the former, natural variation entails the gradual accumulation of minor mutations in alleles. In the latter, lateral gene transfer is an integral mechanism of natural variation. The study of language evolution using biological methods has attracted much interest of late, most approaches focusing on language tree construction. These approaches may underestimate the important role that borrowing plays in language evolution. Network approaches that were originally designed to study lateral gene transfer may provide more realistic insights into the complexities of language evolution. Editor's suggested further reading in BioEssays Linguistic evidence supports date for Homeric epics. © 2014 The Authors. BioEssays Published by WILEY Periodicals, Inc." 139 Puspal Bhabak and Asish Mukhopadhyay. A 3-factor approximation algorithm for a Minimum Acyclic Agreement Forest on k rooted, binary phylogenetic trees. 2014.   Keywords: agreement forest, approximation, explicit network, from rooted trees, phylogenetic network, phylogeny, reconstruction. Note: http://arxiv.org/abs/1407.7125.         140 Zhijiang Li. Fixed-Parameter Algorithm for Hybridization Number of Two Multifurcating Trees. Master's thesis, Dalhousie University, Canada, 2014.   Keywords: agreement forest, explicit network, FPT, from rooted trees, minimum number, phylogenetic network, phylogeny, reconstruction. Note: http://hdl.handle.net/10222/53976.         141 Juan Wang. A new algorithm to construct phylogenetic networks from trees. In Genetics and Molecular Research, Vol. 13(1):1456-1464, 2014.   Keywords: explicit network, from clusters, heuristic, phylogenetic network, Program LNetwork, Program QuickCass, reconstruction. Note: http://dx.doi.org/10.4238/2014.March.6.4.         Toggle abstract "Developing appropriate methods for constructing phylogenetic networks from tree sets is an important problem, and much research is currently being undertaken in this area. BIMLR is an algorithm that constructs phylogenetic networks from tree sets. The algorithm can construct a much simpler network than other available methods. Here, we introduce an improved version of the BIMLR algorithm, QuickCass. QuickCass changes the selection strategy of the labels of leaves below the reticulate nodes, i.e., the nodes with an indegree of at least 2 in BIMLR. We show that QuickCass can construct simpler phylogenetic networks than BIMLR. Furthermore, we show that QuickCass is a polynomial-time algorithm when the output network that is constructed by QuickCass is binary. © FUNPEC-RP." 142 Matthieu Willems, Nadia Tahiri and Vladimir Makarenkov. A new efficient algorithm for inferring explicit hybridization networks following the Neighbor-Joining principle. In JBCB, Vol. 12(5), 2014.   Keywords: explicit network, from distances, heuristic, phylogenetic network, phylogeny, reconstruction.         Toggle abstract "Several algorithms and software have been developed for inferring phylogenetic trees. However, there exist some biological phenomena such as hybridization, recombination, or horizontal gene transfer which cannot be represented by a tree topology. We need to use phylogenetic networks to adequately represent these important evolutionary mechanisms. In this article, we present a new efficient heuristic algorithm for inferring hybridization networks from evolutionary distance matrices between species. The famous Neighbor-Joining concept and the least-squares criterion are used for building networks. At each step of the algorithm, before joining two given nodes, we check if a hybridization event could be related to one of them or to both of them. The proposed algorithm finds the exact tree solution when the considered distance matrix is a tree metric (i.e. it is representable by a unique phylogenetic tree). It also provides very good hybrids recovery rates for large trees (with 32 and 64 leaves in our simulations) for both distance and sequence types of data. The results yielded by the new algorithm for real and simulated datasets are illustrated and discussed in detail. © Imperial College Press." 143 Riccardo Dondi and Yuri Pirola. Beyond Evolutionary Trees. In Ming-Yang Kao editor, Encyclopedia of Algorithms, Pages 1-7, Springer, 2014.   Keywords: explicit network, phylogenetic network, phylogeny, reconstruction, survey.         144 Josh Voorkamp né Collins. Maximal Acyclic Agreement Forests. In JCB, Vol. 21(10):723-731, 2014.   Keywords: agreement forest, explicit network, from rooted trees, hybridization, minimum number, phylogenetic network, phylogeny, reconstruction.         145 Yun Yu, Jianrong Dong, Kevin J. Liu and Luay Nakhleh. Maximum likelihood inference of reticulate evolutionary histories. In PNAS, Vol. 111(46):16448-16453, 2014.   Keywords: explicit network, likelihood, phylogenetic network, phylogeny, reconstruction. Note: http://dx.doi.org/10.1073/pnas.1407950111.         146 Adrià Alcalà Mena, Mercè Llabrés, Francesc Rosselló and Pau Rullan. Tree-Child Cluster Networks. In Fundamenta Informaticae, Vol. 134(1-2):1-15, 2014.   Keywords: explicit network, from clusters, phylogenetic network, phylogeny, Program PhyloNetwork, reconstruction, tree child network.         147 David A. Morrison. Is the Tree of Life the Best Metaphor, Model, or Heuristic for Phylogenetics? In Systematic Biology, Vol. 63(4):628-638, 2014.   Keywords: abstract network, explicit network, phylogenetic network, phylogeny, survey.         148 Katharina Huber and Vincent Moulton. Encoding and Constructing 1-Nested Phylogenetic Networks with Trinets. In ALG, Vol. 66(3):714-738, 2013.   Keywords: explicit network, from trinets, phylogenetic network, phylogeny, reconstruction, uniqueness. Note: http://arxiv.org/abs/1110.0728.         Toggle abstract "Phylogenetic networks are a generalization of phylogenetic trees that are used in biology to represent reticulate or non-treelike evolution. Recently, several algorithms have been developed which aim to construct phylogenetic networks from biological data using triplets, i.e. binary phylogenetic trees on 3-element subsets of a given set of species. However, a fundamental problem with this approach is that the triplets displayed by a phylogenetic network do not necessarily uniquely determine or encode the network. Here we propose an alternative approach to encoding and constructing phylogenetic networks, which uses phylogenetic networks on 3-element subsets of a set, or trinets, rather than triplets. More specifically, we show that for a special, well-studied type of phylogenetic network called a 1-nested network, the trinets displayed by a 1-nested network always encode the network. We also present an efficient algorithm for deciding whether a dense set of trinets (i.e. one that contains a trinet on every 3-element subset of a set) can be displayed by a 1-nested network or not and, if so, constructs that network. In addition, we discuss some potential new directions that this new approach opens up for constructing and comparing phylogenetic networks. © 2012 Springer Science+Business Media, LLC." 149 Leo van Iersel and Simone Linz. A quadratic kernel for computing the hybridization number of multiple trees. In IPL, Vol. 113:318-323, 2013.   Keywords: explicit network, FPT, from rooted trees, kernelization, minimum number, phylogenetic network, phylogeny, Program Clustistic, Program MaafB, Program PIRN, reconstruction. Note: http://arxiv.org/abs/1203.4067, poster.         Toggle abstract "It has recently been shown that the NP-hard problem of calculating the minimum number of hybridization events that is needed to explain a set of rooted binary phylogenetic trees by means of a hybridization network is fixed-parameter tractable if an instance of the problem consists of precisely two such trees. In this paper, we show that this problem remains fixed-parameter tractable for an arbitrarily large set of rooted binary phylogenetic trees. In particular, we present a quadratic kernel. © 2013 Elsevier B.V." 150 Chris Whidden, Robert G. Beiko and Norbert Zeh. Fixed-Parameter Algorithms for Maximum Agreement Forests. In SICOMP, Vol. 42(4):1431-1466, 2013.   Keywords: agreement forest, explicit network, FPT, from rooted trees, hybridization, minimum number, phylogenetic network, phylogeny, Program HybridInterleave, reconstruction, SPR distance. Note: http://arxiv.org/abs/1108.2664, slides.         Toggle abstract "We present new and improved fixed-parameter algorithms for computing maximum agreement forests of pairs of rooted binary phylogenetic trees. The size of such a forest for two trees corresponds to their subtree prune-and-regraft distance and, if the agreement forest is acyclic, to their hybridization number. These distance measures are essential tools for understanding reticulate evolution. Our algorithm for computing maximum acyclic agreement forests is the first depth-bounded search algorithm for this problem. Our algorithms substantially outperform the best previous algorithms for these problems. © 2013 Society for Industrial and Applied Mathematics." 151 Stefan Grünewald, Andreas Spillner, Sarah Bastkowski, Anja Bögershausen and Vincent Moulton. SuperQ: Computing Supernetworks from Quartets. In TCBB, Vol. 10(1):151-160, 2013.   Keywords: abstract network, circular split system, from quartets, heuristic, phylogenetic network, phylogeny, Program QNet, Program SplitsTree, Program SuperQ, software, split network.         Toggle abstract "Supertrees are a commonly used tool in phylogenetics to summarize collections of partial phylogenetic trees. As a generalization of supertrees, phylogenetic supernetworks allow, in addition, the visual representation of conflict between the trees that is not possible to observe with a single tree. Here, we introduce SuperQ, a new method for constructing such supernetworks (SuperQ is freely available at >www.uea.ac.uk/computing/superq.). It works by first breaking the input trees into quartet trees, and then stitching these together to form a special kind of phylogenetic network, called a split network. This stitching process is performed using an adaptation of the QNet method for split network reconstruction employing a novel approach to use the branch lengths from the input trees to estimate the branch lengths in the resulting network. Compared with previous supernetwork methods, SuperQ has the advantage of producing a planar network. We compare the performance of SuperQ to the Z-closure and Q-imputation supernetwork methods, and also present an analysis of some published data sets as an illustration of its applicability. © 2004-2012 IEEE." 152 Stephen J. Willson. Reconstruction of certain phylogenetic networks from their tree-average distances. In BMB, Vol. 75(10):1840-1878, 2013.   Keywords: explicit network, from distances, galled tree, normal network, phylogenetic network, phylogeny, unicyclic network. Note: http://www.public.iastate.edu/~swillson/Tree-AverageReconPaper9.pdf.         Toggle abstract "Trees are commonly utilized to describe the evolutionary history of a collection of biological species, in which case the trees are called phylogenetic trees. Often these are reconstructed from data by making use of distances between extant species corresponding to the leaves of the tree. Because of increased recognition of the possibility of hybridization events, more attention is being given to the use of phylogenetic networks that are not necessarily trees. This paper describes the reconstruction of certain such networks from the tree-average distances between the leaves. For a certain class of phylogenetic networks, a polynomial-time method is presented to reconstruct the network from the tree-average distances. The method is proved to work if there is a single reticulation cycle. © 2013 Society for Mathematical Biology." 153 Yufeng Wu. An Algorithm for Constructing Parsimonious Hybridization Networks with Multiple Phylogenetic Trees. In RECOMB13, Vol. 7821:291-303 of LNCS, springer, 2013.   Keywords: explicit network, exponential algorithm, from rooted trees, phylogenetic network, phylogeny, Program PIRN, reconstruction. Note: http://www.engr.uconn.edu/~ywu/Papers/ExactNetRecomb2013.pdf.         Toggle abstract "Phylogenetic network is a model for reticulate evolution. Hybridization network is one type of phylogenetic network for a set of discordant gene trees, and "displays" each gene tree. A central computational problem on hybridization networks is: given a set of gene trees, reconstruct the minimum (i.e. most parsimonious) hybridization network that displays each given gene tree. This problem is known to be NP-hard, and existing approaches for this problem are either heuristics or make simplifying assumptions (e.g. work with only two input trees or assume some topological properties). In this paper, we develop an exact algorithm (called PIRNC ) for inferring the minimum hybridization networks from multiple gene trees. The PIRNC algorithm does not rely on structural assumptions. To the best of our knowledge, PIRN C is the first exact algorithm for this formulation. When the number of reticulation events is relatively small (say four or fewer), PIRNC runs reasonably efficient even for moderately large datasets. For building more complex networks, we also develop a heuristic version of PIRNC called PIRNCH. Simulation shows that PIRNCH usually produces networks with fewer reticulation events than those by an existing method. © 2013 Springer-Verlag." 154 Miguel Arenas. Computer programs and methodologies for the simulation of DNA sequence data with recombination. In Frontiers in Genetics, Vol. 4(9), 2013.   Keywords: explicit network, phylogenetic network, phylogeny, simulation. Note: http://dx.doi.org/10.3389%2Ffgene.2013.00009.         155 Sha Zhu, James H. Degnan and Bjarki Eldon. Hybrid-Lambda: simulation of multiple merger and Kingman gene genealogies in species networks and species trees. 2013.   Keywords: explicit network, from network, phylogenetic network, phylogeny, Program Hybrid-Lambda, simulation, software. Note: http://arxiv.org/abs/1303.0673.         156 Thi-Hau Nguyen, Vincent Ranwez, Stéphanie Pointet, Anne-Muriel Chifolleau Arigon, Jean-Philippe Doyon and Vincent Berry. Reconciliation and local gene tree rearrangement can be of mutual profit. In ALMOB, Vol. 8(12), 2013.   Keywords: duplication, explicit network, from rooted trees, heuristic, lateral gene transfer, phylogenetic network, phylogeny, Program Mowgli, Program MowgliNNI, Program Prunier, reconstruction, software.         Toggle abstract "Background: Reconciliation methods compare gene trees and species trees to recover evolutionary events such as duplications, transfers and losses explaining the history and composition of genomes. It is well-known that gene trees inferred from molecular sequences can be partly erroneous due to incorrect sequence alignments as well as phylogenetic reconstruction artifacts such as long branch attraction. In practice, this leads reconciliation methods to overestimate the number of evolutionary events. Several methods have been proposed to circumvent this problem, by collapsing the unsupported edges and then resolving the obtained multifurcating nodes, or by directly rearranging the binary gene trees. Yet these methods have been defined for models of evolution accounting only for duplications and losses, i.e. can not be applied to handle prokaryotic gene families.Results: We propose a reconciliation method accounting for gene duplications, losses and horizontal transfers, that specifically takes into account the uncertainties in gene trees by rearranging their weakly supported edges. Rearrangements are performed on edges having a low confidence value, and are accepted whenever they improve the reconciliation cost. We prove useful properties on the dynamic programming matrix used to compute reconciliations, which allows to speed-up the tree space exploration when rearrangements are generated by Nearest Neighbor Interchanges (NNI) edit operations. Experiments on synthetic data show that gene trees modified by such NNI rearrangements are closer to the correct simulated trees and lead to better event predictions on average. Experiments on real data demonstrate that the proposed method leads to a decrease in the reconciliation cost and the number of inferred events. Finally on a dataset of 30 k gene families, this reconciliation method shows a ranking of prokaryotic phyla by transfer rates identical to that proposed by a different approach dedicated to transfer detection [BMCBIOINF 11:324, 2010, PNAS 109(13):4962-4967, 2012].Conclusions: Prokaryotic gene trees can now be reconciled with their species phylogeny while accounting for the uncertainty of the gene tree. More accurate and more precise reconciliations are obtained with respect to previous parsimony algorithms not accounting for such uncertainties [LNCS 6398:93-108, 2010, BIOINF 28(12): i283-i291, 2012].A software implementing the method is freely available at http://www.atgc-montpellier.fr/Mowgli/. © 2013 Nguyen et al.; licensee BioMed Central Ltd." 157 Mukul S. Bansal, Guy Banay, Timothy J. Harlow, J. Peter Gogarten and Ron Shamir. Systematic inference of highways of horizontal gene transfer in prokaryotes. In BIO, Vol. 29(5):571-579, 2013.   Keywords: duplication, explicit network, from species tree, from unrooted trees, lateral gene transfer, phylogenetic network, phylogeny, Program HiDe, Program RANGER-DTL, reconstruction. Note: http://people.csail.mit.edu/mukul/Bansal_Highways_Bioinformatics_2013.pdf.         158 Eric Bapteste, Leo van Iersel, Axel Janke, Scott Kelchner, Steven Kelk, James O. McInerney, David A. Morrison, Luay Nakhleh, Mike Steel, Leen Stougie and James B. Whitfield. Networks: expanding evolutionary thinking. In Trends in Genetics, Vol. 29(8):439-441, 2013.   Keywords: abstract network, explicit network, phylogenetic network, phylogeny, reconstruction. Note: http://bioinf.nuim.ie/wp-content/uploads/2013/06/Bapteste-TiG-2013.pdf.         Toggle abstract "Networks allow the investigation of evolutionary relationships that do not fit a tree model. They are becoming a leading tool for describing the evolutionary relationships between organisms, given the comparative complexities among genomes. © 2013 Elsevier Ltd." 159 Juan Wang, Maozu Guo, Xiaoyan Liu, Yang Liu, Chunyu Wang, Linlin Xing and Kai Che. LNETWORK: An Efficient and Effective Method for Constructing Phylogenetic Networks. In BIO, Vol. 29(18):2269-2276, 2013.   Keywords: explicit network, from rooted trees, phylogenetic network, phylogeny, Program LNetwork, reconstruction, software.         Toggle abstract "Motivation: The evolutionary history of species is traditionally represented with a rooted phylogenetic tree. Each tree comprises a set of clusters, i.e. subsets of the species that are descended from a common ancestor. When rooted phylogenetic trees are built from several different datasets (e.g. from different genes), the clusters are often conflicting. These conflicting clusters cannot be expressed as a simple phylogenetic tree; however, they can be expressed in a phylogenetic network. Phylogenetic networks are a generalization of phylogenetic trees that can account for processes such as hybridization, horizontal gene transfer and recombination, which are difficult to represent in standard tree-like models of evolutionary histories. There is currently a large body of research aimed at developing appropriate methods for constructing phylogenetic networks from cluster sets. The Cass algorithm can construct a much simpler network than other available methods, but is extremely slow for large datasets or for datasets that need lots of reticulate nodes. The networks constructed by Cass are also greatly dependent on the order of input data, i.e. it generally derives different phylogenetic networks for the same dataset when different input orders are used.Results: In this study, we introduce an improved Cass algorithm, Lnetwork, which can construct a phylogenetic network for a given set of clusters. We show that Lnetwork is significantly faster than Cass and effectively weakens the influence of input data order. Moreover, we show that Lnetwork can construct a much simpler network than most of the other available methods. © The Author 2013." 160 Juan Wang, Maozu Guo, Linlin Xing, Kai Che, Xiaoyan Liu and Chunyu Wang. BIMLR: A Method for Constructing Rooted Phylogenetic Networks from Rooted Phylogenetic Trees. In Gene, Vol. 527(1):344-351, 2013.   Keywords: explicit network, from clusters, from rooted trees, phylogenetic network, phylogeny, Program BIMLR, Program Dendroscope, reconstruction, software.         Toggle abstract "Rooted phylogenetic trees constructed from different datasets (e.g. from different genes) are often conflicting with one another, i.e. they cannot be integrated into a single phylogenetic tree. Phylogenetic networks have become an important tool in molecular evolution, and rooted phylogenetic networks are able to represent conflicting rooted phylogenetic trees. Hence, the development of appropriate methods to compute rooted phylogenetic networks from rooted phylogenetic trees has attracted considerable research interest of late. The CASS algorithm proposed by van Iersel et al. is able to construct much simpler networks than other available methods, but it is extremely slow, and the networks it constructs are dependent on the order of the input data. Here, we introduce an improved CASS algorithm, BIMLR. We show that BIMLR is faster than CASS and less dependent on the input data order. Moreover, BIMLR is able to construct much simpler networks than almost all other methods. BIMLR is available at http://nclab.hit.edu.cn/wangjuan/BIMLR/. © 2013 Elsevier B.V." 161 Zhi-Zhong Chen and Lusheng Wang. An Ultrafast Tool for Minimum Reticulate Networks. In JCB, Vol. 20(1):38-41, 2013.   Keywords: agreement forest, explicit network, from rooted trees, phylogenetic network, phylogeny, Program ultra-Net, reconstruction. Note: http://www.cs.cityu.edu.hk/~lwang/research/jcb2013.pdf.         Toggle abstract "Due to hybridization events in evolution, studying different genes of a set of species may yield two or more related but different phylogenetic trees for the set of species. In this case, we want to combine the trees into a reticulate network with the fewest hybridization events. In this article, we develop a software tool (named UltraNet) for several fundamental problems related to the construction of minimum reticulate networks from two or more phylogenetic trees. Our experimental results show that UltraNet is much faster than all previous tools for these problems. © 2013 Mary Ann Liebert, Inc." 162 Willem Sonke. Reconstructing a level-1-network from quartets. 2013.   Keywords: abstract network, from quartets, phylogenetic network, phylogeny, polynomial, Program Fylogenetica, reconstruction, software, visualization. Note: http://alexandria.tue.nl/extra1/afstversl/wsk-i/sonke2013.pdf.         163 Alexey A. Morozov, Yuri P. Galachyants and Yelena V. Likhoshway. Inferring Phylogenetic Networks from Gene Order Data. In BMRI, Vol. 2013(503193):1-7, 2013.   Keywords: abstract network, from distances, from gene order, NeighborNet, phylogenetic network, phylogeny, Program SplitsTree, reconstruction, split decomposition, split network.         Toggle abstract "Existing algorithms allow us to infer phylogenetic networks from sequences (DNA, protein or binary), sets of trees, and distance matrices, but there are no methods to build them using the gene order data as an input. Here we describe several methods to build split networks from the gene order data, perform simulation studies, and use our methods for analyzing and interpreting different real gene order datasets. All proposed methods are based on intermediate data, which can be generated from genome structures under study and used as an input for network construction algorithms. Three intermediates are used: set of jackknife trees, distance matrix, and binary encoding. According to simulations and case studies, the best intermediates are jackknife trees and distance matrix (when used with Neighbor-Net algorithm). Binary encoding can also be useful, but only when the methods mentioned above cannot be used. © 2013 Alexey Anatolievich Morozov et al." 164 Celine Scornavacca, Paprotny Wojciech, Vincent Berry and Vincent Ranwez. Representing a set of reconciliations in a compact way. In JBCB, Vol. 11(2):1250025, 2013.   Keywords: duplication, explicit network, from network, from rooted trees, from species tree, phylogeny, Program GraphDTL, Program TERA, visualization. Note: http://hal-lirmm.ccsd.cnrs.fr/lirmm-00818801.         Toggle abstract "Comparative genomic studies are often conducted by reconciliation analyses comparing gene and species trees. One of the issues with reconciliation approaches is that an exponential number of optimal scenarios is possible. The resulting complexity is masked by the fact that a majority of reconciliation software pick up a random optimal solution that is returned to the end-user. However, the alternative solutions should not be ignored since they tell different stories that parsimony considers as viable as the output solution. In this paper, we describe a polynomial space and time algorithm to build a minimum reconciliation graph-a graph that summarizes the set of all most parsimonious reconciliations. Amongst numerous applications, it is shown how this graph allows counting the number of non-equivalent most parsimonious reconciliations. © 2013 Imperial College Press." 165 Thi-Hau Nguyen. Réconciliations: corriger des arbres de gènes et inférer la fiabilité des événements évolutifs. PhD thesis, Université Montpellier 2, France, 2013.   Keywords: duplication, explicit network, from rooted trees, heuristic, lateral gene transfer, phylogenetic network, phylogeny, Program Mowgli, Program MowgliNNI, reconstruction. Note: http://www.biu-montpellier.fr/florabium/servlet/DocumentFileManager?source=ged&document=ged:IDOCS:247665&resolution=&recordId=theses%3ABIU_THESE%3A1789&file=.         166 David A. Morrison. Phylogenetic networks are fundamentally different from other kinds of biological networks. In WenJun Zhang editor, Network Biology: Theories, Methods and Applications, Chapter 2, Nova Publishers, 2013.   Keywords: abstract network, explicit network, phylogenetic network, phylogeny.         167 Steven Kelk, Simone Linz and David A. Morrison. Fighting network space: it is time for an SQL-type language to filter phylogenetic networks. 2013.   Keywords: database, explicit network, from network, phylogenetic network, phylogeny. Note: http://arxiv.org/abs/1310.6844.         168 Leo van Iersel, Steven Kelk, Nela Lekic and Leen Stougie. A short note on exponential-time algorithms for hybridization number. 2013.   Keywords: explicit network, exponential algorithm, from rooted trees, phylogenetic network, phylogeny, reconstruction. Note: http://arxiv.org/abs/1312.1255.         169 Alberto Apostolico, Matteo Comin, Andreas W. M. Dress and Laxmi Parida. Ultrametric networks: a new tool for phylogenetic analysis. In Algorithms for Molecular Biology, Vol. 8(7):1-10, 2013.   Keywords: abstract network, from distances, phylogenetic network, phylogeny, Program Ultranet. Note: http://dx.doi.org/10.1186/1748-7188-8-7.         Toggle abstract "Background: The large majority of optimization problems related to the inference of distance-based trees used in phylogenetic analysis and classification is known to be intractable. One noted exception is found within the realm of ultrametric distances. The introduction of ultrametric trees in phylogeny was inspired by a model of evolution driven by the postulate of a molecular clock, now dismissed, whereby phylogeny could be represented by a weighted tree in which the sum of the weights of the edges separating any given leaf from the root is the same for all leaves. Both, molecular clocks and rooted ultrametric trees, fell out of fashion as credible representations of evolutionary change. At the same time, ultrametric dendrograms have shown good potential for purposes of classification in so far as they have proven to provide good approximations for additive trees. Most of these approximations are still intractable, but the problem of finding the nearest ultrametric distance matrix to a given distance matrix with respect to the L∞ distance has been long known to be solvable in polynomial time, the solution being incarnated in any minimum spanning tree for the weighted graph subtending to the matrix.Results: This paper expands this subdominant ultrametric perspective by studying ultrametric networks, consisting of the collection of all edges involved in some minimum spanning tree. It is shown that, for a graph with n vertices, the construction of such a network can be carried out by a simple algorithm in optimal time O(n2) which is faster by a factor of n than the direct adaptation of the classical O(n3) paradigm by Warshall for computing the transitive closure of a graph. This algorithm, called UltraNet, will be shown to be easily adapted to compute relaxed networks and to support the introduction of artificial points to reduce the maximum distance between vertices in a pair. Finally, a few experiments will be discussed to demonstrate the applicability of subdominant ultrametric networks.Availability: http://www.dei.unipd.it/~ciompin/main/Ultranet/Ultranet.html. © 2013 Apostolico et al.; licensee BioMed Central Ltd." 170 Mehdi Layeghifard, Pedro R. Peres-Neto and Vladimir Makarenkov. Inferring explicit weighted consensus networks to represent alternative evolutionary histories. In BMCEB, Vol. 13(274):1-25, 2013.   Keywords: explicit network, from rooted trees, from species tree, phylogenetic network, phylogeny, Program ConsensusNetwork, reconstruction. Note: http://dx.doi.org/10.1186/1471-2148-13-274.         Toggle abstract "Background: The advent of molecular biology techniques and constant increase in availability of genetic material have triggered the development of many phylogenetic tree inference methods. However, several reticulate evolution processes, such as horizontal gene transfer and hybridization, have been shown to blur the species evolutionary history by causing discordance among phylogenies inferred from different genes. Methods. To tackle this problem, we hereby describe a new method for inferring and representing alternative (reticulate) evolutionary histories of species as an explicit weighted consensus network which can be constructed from a collection of gene trees with or without prior knowledge of the species phylogeny. Results: We provide a way of building a weighted phylogenetic network for each of the following reticulation mechanisms: diploid hybridization, intragenic recombination and complete or partial horizontal gene transfer. We successfully tested our method on some synthetic and real datasets to infer the above-mentioned evolutionary events which may have influenced the evolution of many species. Conclusions: Our weighted consensus network inference method allows one to infer, visualize and validate statistically major conflicting signals induced by the mechanisms of reticulate evolution. The results provided by the new method can be used to represent the inferred conflicting signals by means of explicit and easy-to-interpret phylogenetic networks. © 2013 Layeghifard et al.; licensee BioMed Central Ltd." 171 Gergely J. Szöllösi, Wojciech Rosikiewicz, Bastien Boussau, Eric Tannier and Vincent Daubin. Efficient Exploration of the Space of Reconciled Gene Trees. In Systematic Biology, Vol. 62(6):901-912, 2013.   Keywords: duplication, explicit network, lateral gene transfer, likelihood, loss, phylogeny, Program ALE, reconstruction. Note: http://arxiv.org/abs/1306.2167.         Toggle abstract "Gene trees record the combination of gene-level events, such as duplication, transfer and loss (DTL), and species-level events, such as speciation and extinction. Gene tree-species tree reconciliation methods model these processes by drawing gene trees into the species tree using a series of gene and species-level events. The reconstruction of gene trees based on sequence alone almost always involves choosing between statistically equivalent or weakly distinguishable relationships that could be much better resolved based on a putative species tree. To exploit this potential for accurate reconstruction of gene trees, the space of reconciled gene trees must be explored according to a joint model of sequence evolution and gene tree-species tree reconciliation. Here we present amalgamated likelihood estimation (ALE), a probabilistic approach to exhaustively explore all reconciled gene trees that can be amalgamated as a combination of clades observed in a sample of gene trees. We implement the ALE approach in the context of a reconciliation model (Szöllo{double acute}si et al. 2013), which allows for the DTL of genes. We use ALE to efficiently approximate the sum of the joint likelihood over amalgamations and to find the reconciled gene tree that maximizes the joint likelihood among all such trees. We demonstrate using simulations that gene trees reconstructed using the joint likelihood are substantially more accurate than those reconstructed using sequence alone. Using realistic gene tree topologies, branch lengths, and alignment sizes, we demonstrate that ALE produces more accurate gene trees even if the model of sequence evolution is greatly simplified. Finally, examining 1099 gene families from 36 cyanobacterial genomes we find that joint likelihood-based inference results in a striking reduction in apparent phylogenetic discord, with respectively. 24%, 59%, and 46% reductions in the mean numbers of duplications, transfers, and losses per gene family. The open source implementation of ALE is available from https://github.com/ssolo/ALE.git. © The Author(s) 2013." 172 Chris Whidden. Efficient Computation and Application of Maximum Agreement Forests. PhD thesis, Dalhousie University, Canada, 2013.   Keywords: agreement forest, explicit network, FPT, from rooted trees, minimum number, phylogenetic network, phylogeny, reconstruction. Note: http://hdl.handle.net/10222/35349.         173 Yufeng Wu. An Algorithm for Constructing Parsimonious Hybridization Networks with Multiple Phylogenetic Trees. In JCB, Vol. 20(10):792-804, 2013.   Keywords: explicit network, exponential algorithm, from rooted trees, phylogenetic network, phylogeny, Program PIRN, reconstruction.         174 Philippe Gambette and Katharina Huber. On Encodings of Phylogenetic Networks of Bounded Level. In JOMB, Vol. 65(1):157-180, 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.archives-ouvertes.fr/hal-00609130/en/.         Toggle abstract "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 well-studied 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 level-1 (phylogenetic) networks we characterize those level-1 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 level-1 networks are not satisfied by networks of higher level. © 2011 Springer-Verlag." 175 Stephen J. Willson. CSD Homomorphisms Between Phylogenetic Networks. In TCBB, Vol. 9(4), 2012.   Keywords: explicit network, from network, from quartets, phylogenetic network. Note: http://www.public.iastate.edu/~swillson/Relationships11IEEE.pdf, preliminary version entitled Relationships Among Phylogenetic Networks.         Toggle abstract "Since Darwin, species trees have been used as a simplified description of the relationships which summarize the complicated network N of reality. Recent evidence of hybridization and lateral gene transfer, however, suggest that there are situations where trees are inadequate. Consequently it is important to determine properties that characterize networks closely related to N and possibly more complicated than trees but lacking the full complexity of N. A connected surjective digraph map (CSD) is a map f from one network N to another network M such that every arc is either collapsed to a single vertex or is taken to an arc, such that f is surjective, and such that the inverse image of a vertex is always connected. CSD maps are shown to behave well under composition. It is proved that if there is a CSD map from N to M, then there is a way to lift an undirected version of M into N, often with added resolution. A CSD map from N to M puts strong constraints on N. In general, it may be useful to study classes of networks such that, for any N, there exists a CSD map from N to some standard member of that class. © 2012 IEEE." 176 Steven Kelk, Celine Scornavacca and Leo van Iersel. On the elusiveness of clusters. In TCBB, Vol. 9(2):517-534, 2012.   Keywords: explicit network, from clusters, from rooted trees, from triplets, level k phylogenetic network, phylogenetic network, phylogeny, Program Clustistic, reconstruction, software. Note: http://arxiv.org/abs/1103.1834.         177 Andreas Spillner, Binh T. Nguyen and Vincent Moulton. Constructing and Drawing Regular Planar Split Networks. In TCBB, Vol. 9(2):395-407, 2012.   Keywords: abstract network, from splits, phylogenetic network, phylogeny, reconstruction, visualization. Note: slides and presentation available at http://www.newton.ac.uk/programmes/PLG/seminars/062111501.html.         Toggle abstract "Split networks are commonly used to visualize collections of bipartitions, also called splits, of a finite set. Such collections arise, for example, in evolutionary studies. Split networks can be viewed as a generalization of phylogenetic trees and may be generated using the SplitsTree package. Recently, the NeighborNet method for generating split networks has become rather popular, in part because it is guaranteed to always generate a circular split system, which can always be displayed by a planar split network. Even so, labels must be placed on the "outside" of the network, which might be problematic in some applications. To help circumvent this problem, it can be helpful to consider so-called flat split systems, which can be displayed by planar split networks where labels are allowed on the inside of the network too. Here, we present a new algorithm that is guaranteed to compute a minimal planar split network displaying a flat split system in polynomial time, provided the split system is given in a certain format. We will also briefly discuss two heuristics that could be useful for analyzing phylogeographic data and that allow the computation of flat split systems in this format in polynomial time. © 2006 IEEE." 178 Paul Phipps and Sergey Bereg. Optimizing Phylogenetic Networks for Circular Split Systems. In TCBB, Vol. 9(2):535-547, 2012.   Keywords: abstract network, from distances, from splits, phylogenetic network, phylogeny, Program PhippsNetwork, reconstruction, software.         Toggle abstract "We address the problem of realizing a given distance matrix by a planar phylogenetic network with a minimum number of faces. With the help of the popular software SplitsTree4, we start by approximating the distance matrix with a distance metric that is a linear combination of circular splits. The main results of this paper are the necessary and sufficient conditions for the existence of a network with a single face. We show how such a network can be constructed, and we present a heuristic for constructing a network with few faces using the first algorithm as the base case. Experimental results on biological data show that this heuristic algorithm can produce phylogenetic networks with far fewer faces than the ones computed by SplitsTree4, without affecting the approximation of the distance matrix. © 2012 IEEE." 179 Andreas Spillner and Vincent Moulton. Optimal algorithms for computing edge weights in planar split-networks. In Journal of Applied Mathematics and Computing, Vol. 39(1-2):1-13, 2012.   Keywords: abstract network, from distances, phylogenetic network, phylogeny, reconstruction, split, split network. Note: http://dx.doi.org/10.1007/s12190-011-0506-z.         Toggle abstract "In phylogenetics, biologists commonly compute split networks when trying to better understand evolutionary data. These graph-theoretical structures represent collections of weighted bipartitions or splits of a finite set, and provide a means to display conflicting evolutionary signals. The weights associated to the splits are used to scale the edges in the network and are often computed using some distance matrix associated with the data. In this paper we present optimal polynomial time algorithms for three basic problems that arise in this context when computing split weights for planar split-networks. These generalize algorithms that have been developed for special classes of split networks (namely, trees and outer-labeled planar networks). As part of our analysis, we also derive a Crofton formula for full flat split systems, structures that naturally arise when constructing planar split-networks. © 2011 Korean Society for Computational and Applied Mathematics." 180 Magnus Bordewich and Charles Semple. Budgeted Nature Reserve Selection with diversity feature loss and arbitrary split systems. In JOMB, Vol. 64(1):69-85, 2012.   Keywords: abstract network, approximation, diversity, phylogenetic network, polynomial, split network. Note: http://www.math.canterbury.ac.nz/~c.semple/papers/BS11.pdf.         Toggle abstract "Arising in the context of biodiversity conservation, the Budgeted Nature Reserve Selection (BNRS) problem is to select, subject to budgetary constraints, a set of regions to conserve so that the phylogenetic diversity (PD) of the set of species contained within those regions is maximized. Here PD is measured across either a single rooted tree or a single unrooted tree. Nevertheless, in both settings, this problem is NP-hard. However, it was recently shown that, for each setting, there is a polynomial-time (1-1/e)-approximation algorithm for it and that this algorithm is tight. In the first part of the paper, we consider two extensions of BNRS. In the rooted setting we additionally allow for the disappearance of features, for varying survival probabilities across species, and for PD to be measured across multiple trees. In the unrooted setting, we extend to arbitrary split systems. We show that, despite these additional allowances, there remains a polynomial-time (1-1/e)-approximation algorithm for each extension. In the second part of the paper, we resolve a complexity problem on computing PD across an arbitrary split system left open by Spillner et al. © 2011 Springer-Verlag." 181 Celine Scornavacca, Simone Linz and Benjamin Albrecht. A first step towards computing all hybridization networks for two rooted binary phylogenetic trees. In JCB, Vol. 19:1227-1242, 2012.   Keywords: agreement forest, explicit network, FPT, from rooted trees, phylogenetic network, phylogeny, Program Dendroscope, Program Hybroscale, reconstruction. Note: http://arxiv.org/abs/1109.3268.         Toggle abstract "Recently, considerable effort has been put into developing fast algorithms to reconstruct a rooted phylogenetic network that explains two rooted phylogenetic trees and has a minimum number of hybridization vertices. With the standard app1235roach to tackle this problem being combinatorial, the reconstructed network is rarely unique. From a biological point of view, it is therefore of importance to not only compute one network, but all possible networks. In this article, we make a first step toward approaching this goal by presenting the first algorithm-called allMAAFs-that calculates all maximum-acyclic-agreement forests for two rooted binary phylogenetic trees on the same set of taxa. © Copyright 2012, Mary Ann Liebert, Inc. 2012." 182 Zhi-Zhong Chen and Lusheng Wang. Algorithms for Reticulate Networks of Multiple Phylogenetic Trees. In TCBB, Vol. 9(2):372-384, 2012.   Keywords: explicit network, from rooted trees, minimum number, phylogenetic network, phylogeny, Program CMPT, Program MaafB, reconstruction, software. Note: http://rnc.r.dendai.ac.jp/~chen/papers/rMaaf.pdf.         Toggle abstract "A reticulate network N of multiple phylogenetic trees may have nodes with two or more parents (called reticulation nodes). There are two ways to define the reticulation number of N. One way is to define it as the number of reticulation nodes in N in this case, a reticulate network with the smallest reticulation number is called an optimal type-I reticulate network of the trees. The better way is to define it as the total number of parents of reticulation nodes in N minus the number of reticulation nodes in N ; in this case, a reticulate network with the smallest reticulation number is called an optimal type-II reticulate network of the trees. In this paper, we first present a fast fixed-parameter algorithm for constructing one or all optimal type-I reticulate networks of multiple phylogenetic trees. We then use the algorithm together with other ideas to obtain an algorithm for estimating a lower bound on the reticulation number of an optimal type-II reticulate network of the input trees. To our knowledge, these are the first fixed-parameter algorithms for the problems. We have implemented the algorithms in ANSI C, obtaining programs CMPT and MaafB. Our experimental data show that CMPT can construct optimal type-I reticulate networks rapidly and MaafB can compute better lower bounds for optimal type-II reticulate networks within shorter time than the previously best program PIRN designed by Wu. © 2006 IEEE." 183 Changiz Eslahchi, Reza Hassanzadeh, Ehsan Mottaghi, Mahnaz Habibi, Hamid Pezeshk and Mehdi Sadeghi. Constructing circular phylogenetic networks from weighted quartets using simulated annealing. In MBIO, Vol. 235(2):123-127, 2012.   Keywords: abstract network, from quartets, heuristic, phylogenetic network, phylogeny, Program SAQ-Net, Program SplitsTree, reconstruction, simulated annealing, software, split network. Note: http://dx.doi.org/10.1016/j.mbs.2011.11.003.         Toggle abstract "In this paper, we present a heuristic algorithm based on the simulated annealing, SAQ-Net, as a method for constructing phylogenetic networks from weighted quartets. Similar to QNet algorithm, SAQ-Net constructs a collection of circular weighted splits of the taxa set. This collection is represented by a split network. In order to show that SAQ-Net performs better than QNet, we apply these algorithm to both the simulated and actual data sets containing salmonella, Bees, Primates and Rubber data sets. Then we draw phylogenetic networks corresponding to outputs of these algorithms using SplitsTree4 and compare the results. We find that SAQ-Net produces a better circular ordering and phylogenetic networks than QNet in most cases. SAQ-Net has been implemented in Matlab and is available for download at http://bioinf.cs.ipm.ac.ir/softwares/saq.net. © 2011 Elsevier Inc." 184 Benjamin Albrecht, Celine Scornavacca, Alberto Cenci and Daniel H. Huson. Fast computation of minimum hybridization networks. In BIO, Vol. 28(2):191-197, 2012.   Keywords: explicit network, from rooted trees, minimum number, phylogenetic network, phylogeny, Program Dendroscope, Program Hybroscale, reconstruction. Note: http://dx.doi.org/10.1093/bioinformatics/btr618.         Toggle abstract "Motivation: Hybridization events in evolution may lead to incongruent gene trees. One approach to determining possible interspecific hybridization events is to compute a hybridization network that attempts to reconcile incongruent gene trees using a minimum number of hybridization events. Results: We describe how to compute a representative set of minimum hybridization networks for two given bifurcating input trees, using a parallel algorithm and provide a user-friendly implementation. A simulation study suggests that our program performs significantly better than existing software on biologically relevant data. Finally, we demonstrate the application of such methods in the context of the evolution of the Aegilops/Triticum genera. Availability and implementation: The algorithm is implemented in the program Dendroscope 3, which is freely available from www.dendroscope.org and runs on all three major operating systems. © The Author 2011. Published by Oxford University Press. All rights reserved." 185 Steven Kelk, Leo van Iersel, Nela Lekic, Simone Linz, Celine Scornavacca and Leen Stougie. Cycle killer... qu'est-ce que c'est? On the comparative approximability of hybridization number and directed feedback vertex set. In SIDMA, Vol. 26(4):1635-1656, 2012.   Keywords: agreement forest, approximation, explicit network, from rooted trees, minimum number, phylogenetic network, phylogeny, Program CycleKiller, reconstruction. Note: http://arxiv.org/abs/1112.5359, about the title.         Toggle abstract "We show that the problem of computing the hybridization number of two rooted binary phylogenetic trees on the same set of taxa X has a constant factor polynomial-time approximation if and only if the problem of computing a minimum-size feedback vertex set in a directed graph (DFVS) has a constant factor polynomial-time approximation. The latter problem, which asks for a minimum number of vertices to be removed from a directed graph to transform it into a directed acyclic graph, is one of the problems in Karp's seminal 1972 list of 21 NP-complete problems. Despite considerable attention from the combinatorial optimization community, it remains to this day unknown whether a constant factor polynomial-time approximation exists for DFVS. Our result thus places the (in)approximability of hybridization number in a much broader complexity context, and as a consequence we obtain that it inherits inapproximability results from the problem Vertex Cover. On the positive side, we use results from the DFVS literature to give an O(log r log log r) approximation for the hybridization number where r is the correct value. Copyright © by SIAM." 186 Philippe Gambette, Vincent Berry and Christophe Paul. Quartets and Unrooted Phylogenetic Networks. In JBCB, Vol. 10(4):1250004, 2012.   Keywords: abstract network, circular split system, explicit network, from quartets, level k phylogenetic network, phylogenetic network, phylogeny, polynomial, reconstruction, split, split network. Note: http://hal.archives-ouvertes.fr/hal-00678046/en/.         Toggle abstract "Phylogenetic networks were introduced to describe evolution in the presence of exchanges of genetic material between coexisting species or individuals. Split networks in particular were introduced as a special kind of abstract network to visualize conflicts between phylogenetic trees which may correspond to such exchanges. More recently, methods were designed to reconstruct explicit phylogenetic networks (whose vertices can be interpreted as biological events) from triplet data. In this article, we link abstract and explicit networks through their combinatorial properties, by introducing the unrooted analog of level-k networks. In particular, we give an equivalence theorem between circular split systems and unrooted level-1 networks. We also show how to adapt to quartets some existing results on triplets, in order to reconstruct unrooted level-k phylogenetic networks. These results give an interesting perspective on the combinatorics of phylogenetic networks and also raise algorithmic and combinatorial questions. © 2012 Imperial College Press." 187 David A. Morrison, Leo van Iersel and Steven Kelk. The Genealogical World of Phylogenetic Networks. Blog, 2012.   Keywords: survey. Note: http://phylonetworks.blogspot.com/.         188 Yun Yu, James H. Degnan and Luay Nakhleh. The probability of a gene tree topology within a phylogenetic network with applications to hybridization detection. In PLoS Genetics, Vol. 8(4):e1002660, 2012.   Keywords: AIC, BIC, explicit network, hybridization, phylogenetic network, phylogeny, statistical model. Note: http://dx.doi.org/10.1371/journal.pgen.1002660.         Toggle abstract "Gene tree topologies have proven a powerful data source for various tasks, including species tree inference and species delimitation. Consequently, methods for computing probabilities of gene trees within species trees have been developed and widely used in probabilistic inference frameworks. All these methods assume an underlying multispecies coalescent model. However, when reticulate evolutionary events such as hybridization occur, these methods are inadequate, as they do not account for such events. Methods that account for both hybridization and deep coalescence in computing the probability of a gene tree topology currently exist for very limited cases. However, no such methods exist for general cases, owing primarily to the fact that it is currently unknown how to compute the probability of a gene tree topology within the branches of a phylogenetic network. Here we present a novel method for computing the probability of gene tree topologies on phylogenetic networks and demonstrate its application to the inference of hybridization in the presence of incomplete lineage sorting. We reanalyze a Saccharomyces species data set for which multiple analyses had converged on a species tree candidate. Using our method, though, we show that an evolutionary hypothesis involving hybridization in this group has better support than one of strict divergence. A similar reanalysis on a group of three Drosophila species shows that the data is consistent with hybridization. Further, using extensive simulation studies, we demonstrate the power of gene tree topologies at obtaining accurate estimates of branch lengths and hybridization probabilities of a given phylogenetic network. Finally, we discuss identifiability issues with detecting hybridization, particularly in cases that involve extinction or incomplete sampling of taxa. © 2012 Yu et al." 189 Hyun Jung Park and Luay Nakhleh. MURPAR: A fast heuristic for inferring parsimonious phylogenetic networks from multiple gene trees. In ISBRA12, Vol. 7292:213-224 of LNCS, springer, 2012.   Keywords: explicit network, from unrooted trees, heuristic, phylogenetic network, phylogeny, reconstruction, software. Note: https://www.researchgate.net/profile/Hyun_Jung_Park2/publication/262318595_MURPAR_A_Fast_Heuristic_for_Inferring_Parsimonious_Phylogenetic_Networks_from_Multiple_Gene_Trees/links/54b7e7b50cf269d8cbf58cc4.pdf.         Toggle abstract "Phylogenetic networks provide a graphical representation of evolutionary histories that involve non-treelike evolutionary events, such as horizontal gene transfer (HGT). One approach for inferring phylogenetic networks is based on reconciling gene trees, assuming all incongruence among the gene trees is due to HGT. Several mathematical results and algorithms, both exact and heuristic, have been introduced to construct and analyze phylogenetic networks. Here, we address the computational problem of inferring phylogenetic networks with minimum reticulations from a collection of gene trees. As this problem is known to be NP-hard even for a pair of gene trees, the problem at hand is very hard. In this paper, we present an efficient heuristic, MURPAR, for inferring a phylogenetic network from a collection of gene trees by using pairwise reconciliations of trees in the collection. Given the development of efficient and accurate methods for pairwise gene tree reconciliations, MURPAR inherits this efficiency and accuracy. Further, the method includes a formulation for combining pairwise reconciliations that is naturally amenable to an efficient integer linear programming (ILP) solution. We show that MURPAR produces more accurate results than other methods and is at least as fast, when run on synthetic and biological data. We believe that our method is especially important for rapidly obtaining estimates of genome-scale evolutionary histories that can be further refined by more detailed and compute-intensive methods. © 2012 Springer-Verlag." 190 Pawel Górecki and Jerzy Tiuryn. Inferring evolutionary scenarios in the duplication, loss and horizontal gene transfer model. In Logic and Program Semantics, Vol. 7230:83-105 of LNCS, springer, 2012.   Keywords: duplication, explicit network, lateral gene transfer, loss, phylogenetic network, phylogeny, reconstruction. Note: http://dx.doi.org/10.1007/978-3-642-29485-3_7.         Toggle abstract "An H-tree is a formal model of evolutionary scenario. It can be used to represent any processes with gene duplication and loss, horizontal gene transfer (HGT) and speciation events. The model of H-trees, introduced in [26], is an extension of the duplication-loss model (DL-model). Similarly to its ancestor, it has a number of interesting mathematical and biological properties. It is, however, more computationally complex than the DL-model. In this paper, we primarily address the problem of inferring H-trees that are compatible with a given gene tree and a given phylogeny of species with HGTs. These results create a mathematical and computational foundation for a more general and practical problem of inferring HGTs from given gene and species trees with HGTs. We also demonstrate how our model can be used to support HGT hypotheses based on empirical data sets. © 2012 Springer-Verlag Berlin Heidelberg." 191 Mukul S. Bansal, Eric J. Alm and Manolis Kellis. Efficient Algorithms for the Reconciliation Problem with Gene Duplication, Horizontal Transfer, and Loss. In ISMB12, Vol. 28(12):i283-i291 of BIO, 2012.   Keywords: duplication, explicit network, from rooted trees, from species tree, lateral gene transfer, loss, phylogenetic network, phylogeny, Program Angst, Program Mowgli, Program RANGER-DTL, reconstruction. Note: http://dx.doi.org/10.1093/bioinformatics/bts225.         Toggle abstract "Motivation: Gene family evolution is driven by evolutionary events such as speciation, gene duplication, horizontal gene transfer and gene loss, and inferring these events in the evolutionary history of a given gene family is a fundamental problem in comparative and evolutionary genomics with numerous important applications. Solving this problem requires the use of a reconciliation framework, where the input consists of a gene family phylogeny and the corresponding species phylogeny, and the goal is to reconcile the two by postulating speciation, gene duplication, horizontal gene transfer and gene loss events. This reconciliation problem is referred to as duplication-transfer-loss (DTL) reconciliation and has been extensively studied in the literature. Yet, even the fastest existing algorithms for DTL reconciliation are too slow for reconciling large gene families and for use in more sophisticated applications such as gene tree or species tree reconstruction.Results: We present two new algorithms for the DTL reconciliation problem that are dramatically faster than existing algorithms, both asymptotically and in practice. We also extend the standard DTL reconciliation model by considering distance-dependent transfer costs, which allow for more accurate reconciliation and give an efficient algorithm for DTL reconciliation under this extended model. We implemented our new algorithms and demonstrated up to 100 000-fold speed-up over existing methods, using both simulated and biological datasets. This dramatic improvement makes it possible to use DTL reconciliation for performing rigorous evolutionary analyses of large gene families and enables its use in advanced reconciliation-based gene and species tree reconstruction methods. © The Author(s) 2012. Published by Oxford University Press." 192 Reza Hassanzadeh, Changiz Eslahchi and Wing-Kin Sung. Constructing phylogenetic supernetworks based on simulated annealing. In MPE, Vol. 63(3):738-744, 2012.   Keywords: abstract network, from unrooted trees, heuristic, phylogenetic network, phylogeny, Program SNSA, reconstruction, simulated annealing, software, split network. Note: http://dx.doi.org/10.1016/j.ympev.2012.02.009.         Toggle abstract Different partial phylogenetic trees can be derived from different sources of evidence and different methods. One important problem is to summarize these partial phylogenetic trees using a supernetwork. We propose a novel simulated annealing based method called SNSA which uses an optimization function to produce a simple network that still retains a great deal of phylogenetic information. We report the performance of this new method on real and simulated datasets. © 2012 Elsevier Inc. 193 Jesper Jansson and Andrzej Lingas. Computing the rooted triplet distance between galled trees by counting triangles. In CPM12, Vol. 7354:385-398 of LNCS, springer, 2012.   Keywords: distance between networks, explicit network, from network, galled tree, phylogenetic network, phylogeny, polynomial, triplet distance. Note: http://www.df.lth.se/~jj/Publications/d_rt_for_Galled_Trees5_CPM_2012.pdf.         Toggle abstract "We consider a generalization of the rooted triplet distance between two phylogenetic trees to two phylogenetic networks. We show that if each of the two given phylogenetic networks is a so-called galled tree with n leaves then the rooted triplet distance can be computed in o(n 2.688) time. Our upper bound is obtained by reducing the problem of computing the rooted triplet distance to that of counting monochromatic and almost- monochromatic triangles in an undirected, edge-colored graph. To count different types of colored triangles in a graph efficiently, we extend an existing technique based on matrix multiplication and obtain several new related results that may be of independent interest. © 2012 Springer-Verlag." 194 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." 195 Leo van Iersel, Steven Kelk, Nela Lekic and Celine Scornavacca. A practical approximation algorithm for solving massive instances of hybridization number. In WABI12, Vol. 7534(430-440) of LNCS, springer, 2012.   Keywords: agreement forest, approximation, explicit network, from rooted trees, hybridization, phylogenetic network, phylogeny, Program CycleKiller, Program Dendroscope, Program HybridNET, reconstruction, software. Note: http://arxiv.org/abs/1205.3417.         Toggle abstract "Reticulate events play an important role in determining evolutionary relationships. The problem of computing the minimum number of such events to explain discordance between two phylogenetic trees is a hard computational problem. In practice, exact solvers struggle to solve instances with reticulation number larger than 40. For such instances, one has to resort to heuristics and approximation algorithms. Here we present the algorithm CycleKiller which is the first approximation algorithm that can produce solutions verifiably close to optimality for instances with hundreds or even thousands of reticulations. Theoretically, the algorithm is an exponential-time 2-approximation (or 4-approximation in its fastest mode). However, using simulations we demonstrate that in practice the algorithm runs quickly for large and difficult instances, producing solutions within one percent of optimality. An implementation of this algorithm, which extends the theoretical work of [14], has been made publicly available. © 2012 Springer-Verlag." 196 Hyun Jung Park and Luay Nakhleh. Inference of reticulate evolutionary histories by maximum likelihood: The performance of information criteria. In RECOMB-CG'12, Vol. 13(suppl 19):S12 of BMCB, 2012.   Keywords: AIC, BIC, explicit network, heuristic, likelihood, phylogenetic network, phylogeny, reconstruction, statistical model. Note: http://www.biomedcentral.com/1471-2105/13/S19/S12.         197 Zhi-Zhong Chen, Lusheng Wang and Satoshi Yamanaka. A fast tool for minimum hybridization networks. In BMCB, Vol. 13:155, 2012.   Keywords: agreement forest, explicit network, from rooted trees, phylogenetic network, phylogeny, Program FastHN, reconstruction, software. Note: http://dx.doi.org/10.1186/1471-2105-13-155.         Toggle abstract "Background: Due to hybridization events in evolution, studying two different genes of a set of species may yield two related but different phylogenetic trees for the set of species. In this case, we want to combine the two phylogenetic trees into a hybridization network with the fewest hybridization events. This leads to three computational problems, namely, the problem of computing the minimum size of a hybridization network, the problem of constructing one minimum hybridization network, and the problem of enumerating a representative set of minimum hybridization networks. The previously best software tools for these problems (namely, Chen and Wang's HybridNet and Albrecht et al.'s Dendroscope 3) run very slowly for large instances that cannot be reduced to relatively small instances. Indeed, when the minimum size of a hybridization network of two given trees is larger than 23 and the problem for the trees cannot be reduced to relatively smaller independent subproblems, then HybridNet almost always takes longer than 1 day and Dendroscope 3 often fails to complete. Thus, a faster software tool for the problems is in need.Results: We develop a software tool in ANSI C, named FastHN, for the following problems: Computing the minimum size of a hybridization network, constructing one minimum hybridization network, and enumerating a representative set of minimum hybridization networks. We obtain FastHN by refining HybridNet with three ideas. The first idea is to preprocess the input trees so that the trees become smaller or the problem becomes to solve two or more relatively smaller independent subproblems. The second idea is to use a fast algorithm for computing the rSPR distance of two given phylognetic trees to cut more branches of the search tree in the exhaustive-search stage of the algorithm. The third idea is that during the exhaustive-search stage of the algorithm, we find two sibling leaves in one of the two forests (obtained from the given trees by cutting some edges) such that they are as far as possible in the other forest. As the result, FastHN always runs much faster than HybridNet. Unlike Dendroscope 3, FastHN is a single-threaded program. Despite this disadvantage, our experimental data shows that FastHN runs substantially faster than the multi-threaded Dendroscope 3 on a PC with multiple cores. Indeed, FastHN can finish within 16 minutes (on average on a Windows-7 (x64) desktop PC with i7-2600 CPU) even if the minimum size of a hybridization network of two given trees is about 25, the trees each have 100 leaves, and the problem for the input trees cannot be reduced to two or more independent subproblems via cluster reductions. It is also worth mentioning that like HybridNet, FastHN does not use much memory (indeed, the amount of memory is at most quadratic in the input size). In contrast, Dendroscope 3 uses a huge amount of memory. Executables of FastHN for Windows XP (x86), Windows 7 (x64), Linux, and Mac OS are available (see the Results and discussion section for details).Conclusions: For both biological datasets and simulated datasets, our experimental results show that FastHN runs substantially faster than HybridNet and Dendroscope 3. The superiority of FastHN in speed over the previous tools becomes more significant as the hybridization number becomes larger. In addition, FastHN uses much less memory than Dendroscope 3 and uses the same amount of memory as HybridNet. © 2012 Chen et al.; licensee BioMed Central Ltd." 198 Michel Habib and Thu-Hien To. Constructing a Minimum Phylogenetic Network from a Dense Triplet Set. In JBCB, Vol. 10(5):1250013, 2012.   Keywords: explicit network, from triplets, level k phylogenetic network, phylogenetic network, phylogeny, polynomial, reconstruction. Note: http://arxiv.org/abs/1103.2266.         Toggle abstract "For a given set L of species and a set T of triplets on L, we seek to construct a phylogenetic network which is consistent with T i.e. which represents all triplets of T. The level of a network is defined as the maximum number of hybrid vertices in its biconnected components. When T is dense, there exist polynomial time algorithms to construct level-0,1 and 2 networks (Aho et al., 1981; Jansson, Nguyen and Sung, 2006; Jansson and Sung, 2006; Iersel et al., 2009). For higher levels, partial answers were obtained in the paper by Iersel and Kelk (2008), with a polynomial time algorithm for simple networks. In this paper, we detail the first complete answer for the general case, solving a problem proposed in Jansson and Sung (2006) and Iersel et al. (2009). For any k fixed, it is possible to construct a level-k network having the minimum number of hybrid vertices and consistent with T, if there is any, in time O(|T| k+1 n⌊4k/3⌋+1). © 2012 Imperial College Press." 199 Ruogu Sheng and Sergey Bereg. Approximating Metrics with Planar Boundary-Labeled Phylogenetic Networks. In JBCB, Vol. 10(6):1250017, 2012.   Keywords: abstract network, from distances, phylogenetic network, phylogeny, reconstruction.         Toggle abstract "Phylogenetic networks are useful for visualizing evolutionary relationships between species with reticulate events such as hybridizations and horizontal gene transfers. In this paper, we consider the problem of constructing undirected phylogenetic networks that (1) are planar graphs and (2) admit embeddings in the plane where the vertices labeling all taxa are on the boundary of the network. We develop a new algorithm for constructing phylogenetic networks satisfying these constraints. First, we show that only approximate networks can be constructed for some distance matrices with at least five taxa. Then we prove that any five-point metric can be represented approximately by a planar boundary-labeled network with guaranteed fit value of 94.79. We extend the networks constructed in the proof to design an algorithm for computing planar boundary-labeled networks for any number of taxa. © 2012 Imperial College Press." 200 Maureen Stolzer, Han Lai, Minli Xu, Deepa Sathaye, Benjamin Vernot and Dannie Durand. Inferring Duplications, Losses, Transfers, and Incomplete Lineage Sorting with Non-Binary Species Trees. In ECCB12, Vol. 28(18):i409-i415 of BIO, 2012.   Keywords: duplication, explicit network, from rooted trees, lateral gene transfer, loss, phylogenetic network, phylogeny, Program Notung, reconstruction. Note: http://dx.doi.org/10.1093/bioinformatics/bts386.         Toggle abstract "Motivation: Gene duplication (D), transfer (T), loss (L) and incomplete lineage sorting (I) are crucial to the evolution of gene families and the emergence of novel functions.The history of these events can be inferred via comparison of gene and species trees, a process called reconciliation, yet current reconciliation algorithms model only a subset of these evolutionary processes. Results: We present an algorithm to reconcile a binary gene tree with a nonbinary species tree under a DTLI parsimony criterion. This is the first reconciliation algorithm to capture all four evolutionary processes driving tree incongruence and the first to reconcile nonbinary species trees with a transfer model. Our algorithm infers all optimal solutions and reports complete, temporally feasible event histories, giving the gene and species lineages in which each event occurred. It is fixed-parameter tractable, with polytime complexity when the maximum species outdegree is fixed. Application of our algorithms to prokaryotic and eukaryotic data show that use of an incomplete event model has substantial impact on the events inferred and resulting biological conclusions. © The Author(s) 2012. Published by Oxford University Press." 201 Hyun Jung Park. Towards Accurate Reconstruction of Phylogenetic Networks. PhD thesis, Rice University, U.S.A., 2012.   Keywords: explicit network, likelihood, parsimony, phylogenetic network, phylogeny, reconstruction. Note: http://scholarship.rice.edu/handle/1911/64705.         202 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.         203 Adrià Alcalà Mena and Francesc Rosselló. Ternary graph isomorphism in polynomial time, after Luks. 2012.   Keywords: distance between networks, explicit network, from network, isomorphism, phylogenetic network, phylogeny, polynomial, Program SAGE. Note: http://arxiv.org/abs/1209.0871.         204 Adrià Alcalà Mena. Trivalent Graph isomorphism in polynomial time. Master's thesis, Universidad de Cantabria, Spain, 2012.   Keywords: distance between networks, explicit network, from network, isomorphism, phylogenetic network, phylogeny, polynomial, Program SAGE. Note: http://arxiv.org/abs/1209.1040.         205 Joseph K. Pickrell and Jonathan K. Pritchard. Inference of Population Splits and Mixtures from Genome-Wide Allele Frequency Data. In PLoS Genetics, Vol. 8(11):e1002967, 2012.   Keywords: explicit network, heuristic, likelihood, phylogenetic network, phylogeny, population genetics, Program TreeMix. Note: http://dx.doi.org/10.1371/journal.pgen.1002967.         Toggle abstract "Many aspects of the historical relationships between populations in a species are reflected in genetic data. Inferring these relationships from genetic data, however, remains a challenging task. In this paper, we present a statistical model for inferring the patterns of population splits and mixtures in multiple populations. In our model, the sampled populations in a species are related to their common ancestor through a graph of ancestral populations. Using genome-wide allele frequency data and a Gaussian approximation to genetic drift, we infer the structure of this graph. We applied this method to a set of 55 human populations and a set of 82 dog breeds and wild canids. In both species, we show that a simple bifurcating tree does not fully describe the data; in contrast, we infer many migration events. While some of the migration events that we find have been detected previously, many have not. For example, in the human data, we infer that Cambodians trace approximately 16% of their ancestry to a population ancestral to other extant East Asian populations. In the dog data, we infer that both the boxer and basenji trace a considerable fraction of their ancestry (9% and 25%, respectively) to wolves subsequent to domestication and that East Asian toy breeds (the Shih Tzu and the Pekingese) result from admixture between modern toy breeds and "ancient" Asian breeds. Software implementing the model described here, called TreeMix, is available at http://treemix.googlecode.com. © 2012 Pickrell, Pritchard." 206 Nick J. Patterson, Priya Moorjani, Yontao Luo, Swapan Mallick, Nadin Rohland, Yiping Zhan, Teri Genschoreck, Teresa Webster and David Reich. Ancient Admixture in Human History. In Genetics, Vol. 192(3):1065-1093, 2012.   Keywords: explicit network, phylogenetic network, phylogeny, population genetics, Program AdmixTools. Note: http://genetics.med.harvard.edu/reich/Reich_Lab/Welcome_files/2012_Patterson_AncientAdmixture_Genetics.pdf.         Toggle abstract "Population mixture is an important process in biology. We present a suite of methods for learning about population mixtures, implemented in a software package called ADMIXTOOLS, that support formal tests for whether mixture occurred and make it possible to infer proportions and dates of mixture. We also describe the development of a new single nucleotide polymorphism (SNP) array consisting of 629,433 sites with clearly documented ascertainment that was specifically designed for population genetic analyses and that we genotyped in 934 individuals from 53 diverse populations. To illustrate the methods, we give a number of examples that provide new insights about the history of human admixture. The most striking finding is a clear signal of admixture into northern Europe, with one ancestral population related to present-day Basques and Sardinians and the other related to present-day populations of northeast Asia and the Americas. This likely reflects a history of admixture between Neolithic migrants and the indigenous Mesolithic population of Europe, consistent with recent analyses of ancient bones from Sweden and the sequencing of the genome of the Tyrolean "Iceman." © 2012 by the Genetics Society of America." 207 Katharina Huber, Vincent Moulton, Andreas Spillner, Sabine Storandt and Radoslaw Suchecki. Computing a consensus of multilabeled trees. In ALENEX12, Pages 84-92, 2012.   Keywords: duplication, explicit network, exponential algorithm, phylogenetic network, phylogeny. Note: http://siam.omnibooksonline.com/2012ALENEX/data/papers/020.pdf.         Toggle abstract In this paper we consider two challenging problems that arise in the context of computing a consensus of a collection of multilabeled trees, namely (1) selecting a compatible collection of clusters on a multiset from an ordered list of such clusters and (2) optimally refining high degree vertices in a multilabeled tree. Forming such a consensus is part of an approach to reconstruct the evolutionary history of a set of species for which events such as genome duplication and hybridization have occurred in the past. We present exact algorithms for solving (1) and (2) that have an exponential run-time in the worst case. To give some impression of their performance in practice, we apply them to simulated input and to a real biological data set highlighting the impact of several structural properties of the input on the performance. 208 Cayla McBee. Generalizing Fourier Calculus on Evolutionary Trees to Splits Networks. In ISPAN'12, Pages 149-155, 2012.   Keywords: abstract network, from sequences, phylogenetic network, phylogeny, split network, statistical model.         Toggle abstract "Biologists have been interested in Phylogenetics, the study of evolutionary relatedness among various groups of organisms, for more than 140 years. In spite of this, it has only been in the last 40 years that advances in technology and the availability of DNA sequences have led to statistical, computational and algorithmic work on determining evolutionary relatedness between organisms. One method of determining historical relationships between organisms is to assume a group based evolutionary model and use a discrete Fourier transform. The 1993 paper 'Fourier Calculus on Evolutionary Trees' by L.A. Szekely, M.A. Steel and P.L. Erdos outlines this process. The transform presented in Szekely et al provides an invertible relationship between phylogenetic trees and expected frequencies of nucleotide patterns in nucleotide sequences. This implies that given a set of nucleotide sequences from various organisms it is possible to construct a phylogenetic tree that represents the historical relationships of those organisms. Some scenarios are poorly described by phylogenetic trees and there are biological and statistical reasons for using networks to model phylogenetic relationships. Given this motivation I have generalized Szekely et al's result to apply to a specific type of phylogenetic network known as a splits network. © 2012 IEEE." 209 Alix Boc. Détection des transferts horizontaux de gènes : modèles et algorithmes appliqués à l'évolution des espèces et des langues. PhD thesis, Université du Québec à Montréal, Canada, 2012.   Keywords: explicit network, from rooted trees, from species tree, phylogenetic network, phylogeny, Program T REX, reconstruction. Note: http://www.collectionscanada.gc.ca/obj/thesescanada/vol2/QMUQ/TC-QMUQ-4658.pdf.         210