Who is Who in Phylogenetic Networks

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1 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/.         2 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.         3 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.         4 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.         5 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." 6 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.         7 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." 8 Joel Sjöstrand, Ali Tofigh, Vincent Daubin, Lars Arvestad, Bengt Sennblad and Jens Lagergren. A Bayesian Method for Analyzing Lateral Gene Transfer. In Systematic Biology, Vol. 63(3):409-420, 2014.   Keywords: bayesian, duplication, from rooted trees, from sequences, from species tree, lateral gene transfer, loss, phylogenetic network, phylogeny, Program JPrIME-DLTRS, reconstruction. Note: http://dx.doi.org/10.1093/sysbio/syu007.         9 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.         10 Yun Yu, R. Matthew Barnett and Luay Nakhleh. Parsimonious Inference of Hybridization in the Presence of Incomplete Lineage Sorting. In Systematic Biology, Vol. 62(5):738-751, 2013.   Keywords: from network, from rooted trees, hybridization, lineage sorting, parsimony, phylogenetic network, phylogeny, Program PhyloNet, reconstruction.         Toggle abstract "Hybridization plays an important evolutionary role in several groups of organisms. A phylogenetic approach to detect hybridization entails sequencing multiple loci across the genomes of a group of species of interest, reconstructing their gene trees, and taking their differences as indicators of hybridization. However, methods that follow this approach mostly ignore population effects, such as incomplete lineage sorting (ILS). Given that hybridization occurs between closely related organisms, ILS may very well be at play and, hence, must be accounted for in the analysis framework. To address this issue, we present a parsimony criterion for reconciling gene trees within the branches of a phylogenetic network, and a local search heuristic for inferring phylogenetic networks from collections of gene-tree topologies under this criterion. This framework enables phylogenetic analyses while accounting for both hybridization and ILS. Further, we propose two techniques for incorporating information about uncertainty in gene-tree estimates. Our simulation studies demonstrate the good performance of our framework in terms of identifying the location of hybridization events, as well as estimating the proportions of genes that underwent hybridization. Also, our framework shows good performance in terms of efficiency on handling large data sets in our experiments. Further, in analysing a yeast data set, we demonstrate issues that arise when analysing real data sets. Although a probabilistic approach was recently introduced for this problem, and although parsimonious reconciliations have accuracy issues under certain settings, our parsimony framework provides a much more computationally efficient technique for this type of analysis. Our framework now allows for genome-wide scans for hybridization, while also accounting for ILS. [Phylogenetic networks; hybridization; incomplete lineage sorting; coalescent; multi-labeled trees.] © 2013 The Author(s). All rights reserved." 11 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.         12 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." 13 Daniel H. Huson and Celine Scornavacca. Dendroscope 3: An Interactive Tool for Rooted Phylogenetic Trees and Networks. In Systematic Biology, Vol. 61(6):1061-1067, 2012.   Keywords: from rooted trees, from triplets, phylogenetic network, phylogeny, Program Dendroscope, reconstruction, software, visualization.         Toggle abstract "Dendroscope 3 is a new program for working with rooted phylogenetic trees and networks. It provides a number of methods for drawing and comparing rooted phylogenetic networks, and for computing them from rooted trees. The program can be used interactively or in command-line mode. The program is written in Java, use of the software is free, and installers for all 3 major operating systems can be downloaded from www.dendroscope.org. [Phylogenetic trees; phylogenetic networks; software.] © 2012 The Author(s)." 14 Daniel H. Huson and Celine Scornavacca. A survey of combinatorial methods for phylogenetic networks. In Genome Biology and Evolution, Vol. 3:23-35, 2011.   Keywords: phylogenetic network, survey. Note: http://dx.doi.org/10.1093/gbe/evq077.         Toggle abstract "The evolutionary history of a set of species is usually described by a rooted phylogenetic tree. Although it is generally undisputed that bifurcating speciation events and descent with modifications are major forces of evolution, there is a growing belief that reticulate events also have a role to play. Phylogenetic networks provide an alternative to phylogenetic trees and may be more suitable for data sets where evolution involves significant amounts of reticulate events, such as hybridization, horizontal gene transfer, or recombination. In this article, we give an introduction to the topic of phylogenetic networks, very briefly describing the fundamental concepts and summarizing some of the most important combinatorial methods that are available for their computation. © 2010 The Author(s)." 15 Luay Nakhleh. Evolutionary phylogenetic networks: models and issues. In L. Heath and N. Ramakrishnan editors, The Problem Solving Handbook for Computational Biology and Bioinformatics, Springer, 2010.   Keywords: phylogenetic network, phylogeny, survey. Note: http://www.cs.rice.edu/~nakhleh/Papers/HeathRamakrishnanBookChapter.pdf.         16 Joel Velasco and Elliott Sober. Testing for Treeness: Lateral Gene Transfer, Phylogenetic Inference, and Model Selection. In Biology and Philosophy, Vol. 25(4):675-687, 2010.   Keywords: explicit network, model selection, phylogenetic network, phylogeny, reconstruction, statistical model. Note: http://joelvelasco.net/Papers/velascosober-testingfortreeness.pdf.         Toggle abstract "A phylogeny that allows for lateral gene transfer (LGT) can be thought of as a strictly branching tree (all of whose branches are vertical) to which lateral branches have been added. Given that the goal of phylogenetics is to depict evolutionary history, we should look for the best supported phylogenetic network and not restrict ourselves to considering trees. However, the obvious extensions of popular tree-based methods such as maximum parsimony and maximum likelihood face a serious problem-if we judge networks by fit to data alone, networks that have lateral branches will always fit the data at least as well as any network that restricts itself to vertical branches. This is analogous to the well-studied problem of overfitting data in the curve-fitting problem. Analogous problems often have analogous solutions and we propose to treat network inference as a case of model selection and use the Akaike Information Criterion (AIC). Strictly tree-like networks are more parsimonious than those that postulate lateral as well as vertical branches. This leads to the conclusion that we should not always infer LGT events whenever it would improve our fit-to-data, but should do so only when the improved fit is larger than the penalty for adding extra lateral branches. © 2010 Springer Science+Business Media B.V." 17 Robert G. Beiko. Gene sharing and genome evolution: networks in trees and trees in networks. In Biology and Philosophy, Vol. 25(4):659-673, 2010.   Keywords: abstract network, explicit network, from rooted trees, galled network, phylogenetic network, phylogeny, Program Dendroscope, Program SplitsTree, reconstruction, split network, survey. Note: http://dx.doi.org/10.1007/s10539-010-9217-3.         Toggle abstract "Frequent lateral genetic transfer undermines the existence of a unique "tree of life" that relates all organisms. Vertical inheritance is nonetheless of vital interest in the study of microbial evolution, and knowing the "tree of cells" can yield insights into ecological continuity, the rates of change of different cellular characters, and the evolutionary plasticity of genomes. Notwithstanding within-species recombination, the relationships most frequently recovered from genomic data at shallow to moderate taxonomic depths are likely to reflect cellular inheritance. At the same time, it is clear that several types of 'average signals' from whole genomes can be highly misleading, and the existence of a central tendency must not be taken as prima facie evidence of vertical descent. Phylogenetic networks offer an attractive solution, since they can be formulated in ways that mitigate the misleading aspects of hybrid evolutionary signals in genomes. But the connections in a network typically show genetic relatedness without distinguishing between vertical and lateral inheritance of genetic material. The solution may lie in a compromise between strict tree-thinking and network paradigms: build a phylogenetic network, but identify the set of connections in the network that are potentially due to vertical descent. Even if a single tree cannot be unambiguously identified, choosing a subnetwork of putative vertical connections can still lead to drastic reductions in the set of candidate vertical hypotheses. © 2010 Springer Science+Business Media B.V." 18 David A. Morrison. Phylogenetic networks in systematic biology (and elsewhere) In R.M. Mohan editor, Research Advances in Systematic Biology, Global Research Network, Trivandrum, India, 2010.   Keywords: abstract network, explicit network, phylogenetic network, phylogeny, reconstruction, survey.         19 Marta Melé, Asif Javed, Marc Pybus, Francesc Calafell, Laxmi Parida, Jaume Bertranpetit and Genographic Consortium. A New Method to Reconstruct Recombination Events at a Genomic Scale. In PLoS Computational Biology, Vol. 6(11):e1001010, 2010.   Keywords: explicit network, from sequences, phylogenetic network, phylogeny. Note: http://dx.doi.org/10.1371/journal.pcbi.1001010.         Toggle abstract "Recombination is one of the main forces shaping genome diversity, but the information it generates is often overlooked. A recombination event creates a junction between two parental sequences that may be transmitted to the subsequent generations. Just like mutations, these junctions carry evidence of the shared past of the sequences. We present the IRiS algorithm, which detects past recombination events from extant sequences and specifies the place of each recombination and which are the recombinants sequences. We have validated and calibrated IRiS for the human genome using coalescent simulations replicating standard human demographic history and a variable recombination rate model, and we have finetuned IRiS parameters to simultaneously optimize for false discovery rate, sensitivity, and accuracy in placing the recombination events in the sequence. Newer recombinations overwrite traces of past ones and our results indicate more recent recombinations are detected by IRiS with greater sensitivity. IRiS analysis of the MS32 region, previously studied using sperm typing, showed good concordance with estimated recombination rates. We also applied IRiS to haplotypes for 18 X-chromosome regions in HapMap Phase 3 populations. Recombination events detected for each individual were recoded as binary allelic states and combined into recotypes. Principal component analysis and multidimensional scaling based on recotypes reproduced the relationships between the eleven HapMap Phase III populations that can be expected from known human population history, thus further validating IRiS. We believe that our new method will contribute to the study of the distribution of recombination events across the genomes and, for the first time, it will allow the use of recombination as genetic marker to study human genetic variation. © 2010 Mele ́ et al." 20 Robert G. Beiko and Mark A. Ragan. Untangling Hybrid Phylogenetic Signals: Horizontal Gene Transfer and Artifacts of Phylogenetic Reconstruction. In Horizontal Gene Transfer, Vol. 532:241-256 of Methods in Molecular Biology, 2009.   Note: http://dx.doi.org/10.1007/978-1-60327-853-9_14.         Toggle abstract "Phylogenomic methods can be used to investigate the tangled evolutionary relationships among genomes. Building 'all the trees of all the genes' can potentially identify common pathways of horizontal gene transfer (HGT) among taxa at varying levels of phylogenetic depth. Phylogenetic affinities can be aggregated and merged with the information about genetic linkage and biochemical function to examine hypotheses of adaptive evolution via HGT. Additionally, the use of many genetic data sets increases the power of statistical tests for phylogenetic artifacts. However, large-scale phylogenetic analyses pose several challenges, including the necessary abandonment of manual validation techniques, the need to translate inferred phylogenetic discordance into inferred HGT events, and the challenges involved in aggregating results from search-based inference methods. In this chapter we describe a tree search procedure to recover the most parsimonious pathways of HGT, and examine some of the assumptions that are made by this method." 21 Mark A. Ragan. Trees and networks before and after Darwin. In Biology Direct, Vol. 4(43), 2009.   Keywords: abstract network, explicit network, phylogenetic network, phylogeny, survey, visualization. Note: http://dx.doi.org/10.1186/1745-6150-4-43.         Toggle abstract "It is well-known that Charles Darwin sketched abstract trees of relationship in his 1837 notebook, and depicted a tree in the Origin of Species (1859). Here I attempt to place Darwin's trees in historical context. By the mid-Eighteenth century the Great Chain of Being was increasingly seen to be an inadequate description of order in nature, and by about 1780 it had been largely abandoned without a satisfactory alternative having been agreed upon. In 1750 Donati described aquatic and terrestrial organisms as forming a network, and a few years later Buffon depicted a network of genealogical relationships among breeds of dogs. In 1764 Bonnet asked whether the Chain might actually branch at certain points, and in 1766 Pallas proposed that the gradations among organisms resemble a tree with a compound trunk, perhaps not unlike the tree of animal life later depicted by Eichwald. Other trees were presented by Augier in 1801 and by Lamarck in 1809 and 1815, the latter two assuming a transmutation of species over time. Elaborate networks of affinities among plants and among animals were depicted in the late Eighteenth and very early Nineteenth centuries. In the two decades immediately prior to 1837, so-called affinities and/or analogies among organisms were represented by diverse geometric figures. Series of plant and animal fossils in successive geological strata were represented as trees in a popular textbook from 1840, while in 1858 Bronn presented a system of animals, as evidenced by the fossil record, in a form of a tree. Darwin's 1859 tree and its subsequent elaborations by Haeckel came to be accepted in many but not all areas of biological sciences, while network diagrams were used in others. Beginning in the early 1960s trees were inferred from protein and nucleic acid sequences, but networks were re-introduced in the mid-1990s to represent lateral genetic transfer, increasingly regarded as a fundamental mode of evolution at least for bacteria and archaea. In historical context, then, the Network of Life preceded the Tree of Life and might again supersede it. Reviewers: This article was reviewed by Eric Bapteste, Patrick Forterre and Dan Graur. © 2009 Ragan; licensee BioMed Central Ltd." 22 Gabriel Valiente. Combinatorial Pattern Matching Algorithms in Computational Biology Using Perl and R. Pages 184-208, Taylor & Francis/CRC Press, 2009.   Keywords: counting, distance between networks, galled tree, generation, phylogenetic network, phylogeny, survey, time consistent network, tree child network, tree sibling network. Note: http://books.google.fr/books?id=F4YIIUWb7yMC.         23 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.         24 Chen Meng and Laura S. Kubatko. Detecting hybrid speciation in the presence of incomplete lineage sorting using gene tree incongruence: A model. In Theoretical Population Biology, Vol. 75(1):35-45, 2009.   Keywords: bayesian, coalescent, from network, from rooted trees, hybridization, likelihood, lineage sorting, phylogenetic network, phylogeny, statistical model. Note: http://dx.doi.org/10.1016/j.tpb.2008.10.004.         Toggle abstract "The application of phylogenetic inference methods, to data for a set of independent genes sampled randomly throughout the genome, often results in substantial incongruence in the single-gene phylogenetic estimates. Among the processes known to produce discord between single-gene phylogenies, two of the best studied in a phylogenetic context are hybridization and incomplete lineage sorting. Much recent attention has focused on the development of methods for estimating species phylogenies in the presence of incomplete lineage sorting, but phylogenetic models that allow for hybridization have been more limited. Here we propose a model that allows incongruence in single-gene phylogenies to be due to both hybridization and incomplete lineage sorting, with the goal of determining the contribution of hybridization to observed gene tree incongruence in the presence of incomplete lineage sorting. Using our model, we propose methods for estimating the extent of the role of hybridization in both a likelihood and a Bayesian framework. The performance of our methods is examined using both simulated and empirical data. © 2008 Elsevier Inc. All rights reserved." 25 Bui Quang Minh, Steffen Klaere and Arndt von Haeseler. Taxon Selection under Split Diversity. In Systematic Biology, Vol. 58(6):586-594, 2009.   Keywords: abstract network, circular split system, diversity, from network, phylogenetic network, split network. Note: http://dx.doi.org/10.1093/sysbio/syp058.         Toggle abstract "The phylogenetic diversity (PD) measure of biodiversity is evaluated using a phylogenetic tree, usually inferred from morphological or molecular data. Consequently, it is vulnerable to errors in that tree, including those resulting from sampling error, model misspecification, or conflicting signals. To improve the robustness of PD, we can evaluate the measure using either a collection (or distribution) of trees or a phylogenetic network. Recently, it has been shown that these 2 approaches are equivalent but that the problem of maximizing PD in the general concept is NP-hard. In this study, we provide an efficient dynamic programming algorithm for maximizing PD when splits in the trees or network form a circular split system. We illustrate our method using a case study of game birds (Galliformes) and discuss the different choices of taxa based on our approach and PD." 26 Leo van Iersel, Judith Keijsper, Steven Kelk, Leen Stougie, Ferry Hagen and Teun Boekhout. Constructing level-2 phylogenetic networks from triplets. In RECOMB08, Vol. 4955:450-462 of LNCS, springer, 2008.   Keywords: explicit network, from triplets, level k phylogenetic network, NP complete, phylogenetic network, phylogeny, polynomial, Program Level2, reconstruction. Note: http://homepages.cwi.nl/~iersel/level2full.pdf. An appendix with proofs can be found here http://arxiv.org/abs/0707.2890.         Toggle abstract "Jansson and Sung showed that, given a dense set of input triplets T (representing hypotheses about the local evolutionary relationships of triplets of taxa), it is possible to determine in polynomial time whether there exists a level-1 network consistent with T, and if so, to construct such a network [24]. Here, we extend this work by showing that this problem is even polynomial time solvable for the construction of level-2 networks. This shows that, assuming density, it is tractable to construct plausible evolutionary histories from input triplets even when such histories are heavily nontree-like. This further strengthens the case for the use of triplet-based methods in the construction of phylogenetic networks. We also implemented the algorithm and applied it to yeast data. © 2009 IEEE." 27 Steven M. Woolley, David Posada and Keith A. Crandall. A Comparison of Phylogenetic Network Methods Using Computer Simulation. In PLoS ONE, Vol. 3(4):e1913, 2008.   Keywords: abstract network, distance between networks, evaluation, median network, MedianJoining, minimum spanning network, NeighborNet, parsimony, phylogenetic network, phylogeny, Program Arlequin, Program CombineTrees, Program Network, Program SHRUB, Program SplitsTree, Program TCS, split decomposition. Note: http://dx.doi.org/10.1371/journal.pone.0001913.         Toggle abstract "Background: We present a series of simulation studies that explore the relative performance of several phylogenetic network approaches (statistical parsimony, split decomposition, union of maximum parsimony trees, neighbor-net, simulated history recombination upper bound, median-joining, reduced median joining and minimum spanning network) compared to standard tree approaches (neighbor-joining and maximum parsimony) in the presence and absence of recombination. Principal Findings: In the absence of recombination, all methods recovered the correct topology and branch lengths nearly all of the time when the subtitution rate was low, except for minimum spanning networks, which did considerably worse. At a higher substitution rate, maximum parsimony and union of maximum parsimony trees were the most accurate. With recombination, the ability to infer the correct topology was halved for all methods and no method could accurately estimate branch lengths. Conclusions: Our results highlight the need for more accurate phylogenetic network methods and the importance of detecting and accounting for recombination in phylogenetic studies. Furthermore, we provide useful information for choosing a network algorithm and a framework in which to evaluate improvements to existing methods and novel algorithms developed in the future. © 2008 Woolley et al." 28 James B. Whitfield, Sydney A. Cameron, Daniel H. Huson and Mike Steel. Filtered Z-Closure Supernetworks for Extracting and Visualizing Recurrent Signal from Incongruent Gene Trees. In Systematic Biology, Vol. 57(6):939-947, 2008.   Keywords: abstract network, from unrooted trees, phylogenetic network, phylogeny, Program SplitsTree, split, split network, supernetwork. Note: http://www.life.uiuc.edu/scameron/pdfs/Filtered%20Z-closure%20SystBiol.pdf.         29 Gabriel Cardona, Francesc Rosselló and Gabriel Valiente. Extended Newick: It is Time for a Standard Representation. In BMCB, Vol. 9:532, 2008.   Keywords: evaluation, explicit network, phylogenetic network, Program Bio PhyloNetwork, Program Dendroscope, Program NetGen, Program PhyloNet, Program SplitsTree, Program TCS, visualization. Note: http://bioinfo.uib.es/media/uploaded/bmc-2008-enewick-sub.pdf.         30 Barbara R. Holland, Glenn Conner, Katharina Huber and Vincent Moulton. Imputing Supertrees and Supernetworks from Quartets. In Systematic Biology, Vol. 56(1):57-67, 2007.   Keywords: abstract network, from unrooted trees, phylogenetic network, phylogeny, Program Quartet, reconstruction, split network, supernetwork. Note: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.99.3215.         Toggle abstract "Inferring species phylogenies is an important part of understanding molecular evolution. Even so, it is well known that an accurate phylogenetic tree reconstruction for a single gene does not always necessarily correspond to the species phylogeny. One commonly accepted strategy to cope with this problem is to sequence many genes; the way in which to analyze the resulting collection of genes is somewhat more contentious. Supermatrix and supertree methods can be used, although these can suppress conflicts arising from true differences in the gene trees caused by processes such as lineage sorting, horizontal gene transfer, or gene duplication and loss. In 2004, Huson et al. (IEEE/ACM Trans. Comput. Biol. Bioinformatics 1:151-158) presented the Z-closure method that can circumvent this problem by generating a supernetwork as opposed to a supertree. Here we present an alternative way for generating supernetworks called Q-imputation. In particular, we describe a method that uses quartet information to add missing taxa into gene trees. The resulting trees are subsequently used to generate consensus networks, networks that generalize strict and majority-rule consensus trees. Through simulations and application to real data sets, we compare Q-imputation to the matrix representation with parsimony (MRP) supertree method and Z-closure, and demonstrate that it provides a useful complementary tool. Copyright © Society of Systematic Biologists." 31 Monique M. Morin. Phylogenetic Networks: Simulation, Characterization, and Reconstruction. PhD thesis, The University of New Mexico, U.S.A., 2007.   Keywords: evaluation, explicit network, hybridization, lateral gene transfer, phylogenetic network, phylogeny, Program NetGen, simulation, software. Note: http://www.cs.unm.edu/~morin/morin_phd.pdf.         32 Tamir Tuller and Sagi Snir. The NET-HMM: a HMM Based Likelihood Model for Evolutionary Networks. 2007.   Keywords: lateral gene transfer, likelihood, phylogenetic network, phylogeny, reconstruction, statistical model. Note: Poster presented at the eleventh Annual International Conference on Research in Computational Molecular Biology (RECOMB'07), http://www.qb3.org/recomb07/posters/Tuller013043013RECOMB_HMM1.pdf.         33 Galina Glazko, Vladimir Makarenkov, Jing Liu and Arcady Mushegian. Evolutionary history of bacteriophages with double-stranded DNA genomes. In Biology Direct, Vol. 2(36), 2007.   Keywords: explicit network, from sequences, phylogenetic network, phylogeny, Program T REX. Note: http://dx.doi.org/10.1186/1745-6150-2-36.         Toggle abstract "Background: Reconstruction of evolutionary history of bacteriophages is a difficult problem because of fast sequence drift and lack of omnipresent genes in phage genomes. Moreover, losses and recombinational exchanges of genes are so pervasive in phages that the plausibility of phylogenetic inference in phage kingdom has been questioned. Results: We compiled the profiles of presence and absence of 803 orthologous genes in 158 completely sequenced phages with double-stranded DNA genomes and used these gene content vectors to infer the evolutionary history of phages. There were 18 well-supported clades, mostly corresponding to accepted genera, but in some cases appearing to define new taxonomic groups. Conflicts between this phylogeny and trees constructed from sequence alignments of phage proteins were exploited to infer 294 specific acts of intergenome gene transfer. Conclusion: A notoriously reticulate evolutionary history of fast-evolving phages can be reconstructed in considerable detail by quantitative comparative genomics. © 2007 Glazko et al; licensee BioMed Central Ltd." 34 Nicolas Galtier. A model of horizontal gene transfer and the bacterial phylogeny problem. In Systematic Biology, Vol. 56(4):633-642, 2007.   Keywords: explicit network, generation, lateral gene transfer, phylogenetic network, phylogeny, Program HGT_simul, software, statistical model. Note: http://dx.doi.org/10.1080/10635150701546231.         Toggle abstract "How much horizontal gene transfer (HGT) between species influences bacterial phylogenomics is a controversial issue. This debate, however, lacks any quantitative assessment of the impact of HGT on phylogenies and of the ability of tree-building methods to cope with such events. I introduce a Markov model of genome evolution with HGT, accounting for the constraints on time-an HGT event can only occur between concomitantly living species. This model is used to simulate multigene sequence data sets with or without HGT. The consequences of HGT on phylogenomic inference are analyzed and compared to other well-known phylogenetic artefacts. It is found that supertree methods are quite robust to HGT, keeping high levels of performance even when gene trees are largely incongruent with each other. Gene tree incongruence per se is not indicative of HGT. HGT, however, removes the (otherwise observed) positive relationship between sequence length and gene tree congruence to the estimated species tree. Surprisingly, when applied to a bacterial and a eukaryotic multigene data set, this criterion rejects the HGT hypothesis for the former, but not the latter data set. Copyright © Society of Systematic Biologists." 35 Mihaela Baroni, Charles Semple and Mike Steel. Hybrids in Real Time. In Systematic Biology, Vol. 55(1):46-56, 2006.   Keywords: agreement forest, from rooted trees, phylogenetic network, phylogeny, polynomial, reconstruction, time consistent network. Note: http://www.math.canterbury.ac.nz/~m.steel/Non_UC/files/research/hybrids.pdf.         Toggle abstract "We describe some new and recent results that allow for the analysis and representation of reticulate evolution by nontree networks. In particular, we (1) present a simple result to show that, despite the presence of reticulation, there is always a well-defined underlying tree that corresponds to those parts of life that do not have a history of reticulation; (2) describe and apply new theory for determining the smallest number of hybridization events required to explain conflicting gene trees; and (3) present a new algorithm to determine whether an arbitrary rooted network can be realized by contemporaneous reticulation events. We illustrate these results with examples. Copyright © Society of Systematic Biologists." 36 Guillaume Bourque and Louxin Zhang. Models and Methods in Comparative Genomics. In Chau-Wen Tseng editor, Advances in Computers, Special Volume: Computational Biology, Vol. 68, Elsevier, 2006.   Keywords: from distances, from rooted trees, from sequences, galled tree, phylogenetic network, phylogeny, survey. Note: http://www.math.nus.edu.sg/~matzlx/papers/CompGen_ZLX.pdf.         37 Martyn Kennedy, Barbara R. Holland, Russel D. Gray and Hamish G. Spencer. Untangling Long Branches: Identifying Conflicting Phylogenetic Signals Using Spectral Analysis, Neighbor-Net, and Consensus Networks. In Systematic Biology, Vol. 54(4):620-633, 2005.   Keywords: abstract network, consensus, NeighborNet, phylogenetic network, phylogeny. Note: http://awcmee.massey.ac.nz/people/bholland/pdf/Kennedy_etal_2005.pdf.         38 David A. Morrison. Networks in phylogenetic analysis: new tools for population biology. In IJP, Vol. 35:567-582, 2005.   Keywords: median network, NeighborNet, phylogenetic network, phylogeny, population genetics, Program Network, Program Spectronet, Program SplitsTree, Program T REX, Program TCS, reconstruction, reticulogram, split decomposition, survey. Note: http://hem.fyristorg.com/acacia/papers/networks.pdf.         39 Richard C. Winkworth, David Bryant, Peter J. Lockhart, David Havell and Vincent Moulton. Biogeographic Interpretation of Splits Graphs: Least Squares Optimization of Branch Lengths. In Systematic Biology, Vol. 54(1):56-65, 2005.   Keywords: abstract network, from distances, from network, phylogenetic network, phylogeny, reconstruction, split, split network. Note: http://www.math.auckland.ac.nz/~bryant/Papers/05Biogeographic.pdf.         40 Insa Cassens, Patrick Mardulyn and Michel C. Milinkovitch. Evaluating Intraspecific Network Construction Methods Using Simulated Sequence Data: Do Existing Algorithms Outperform the Global Maximum Parsimony Approach? In Systematic Biology, Vol. 54(3):363-372, 2005.   Keywords: abstract network, evaluation, from unrooted trees, haplotype network, parsimony, phylogenetic network, phylogeny, Program Arlequin, Program CombineTrees, Program Network, Program TCS, reconstruction, software. Note: http://www.lanevol.org/LANE/publications_files/Cassens_etal_SystBio_2005.pdf.         41 David Bryant. Extending tree models to splits networks. In Lior Pachter and Bernd Sturmfels editors, Algebraic Statistics for Computational Biology, Pages 322-334, Cambridge University Press, 2005.   Keywords: abstract network, from splits, likelihood, phylogenetic network, phylogeny, split, split network, statistical model. Note: http://www.math.auckland.ac.nz/~bryant/Papers/05ascbChapter.pdf.         42 Pierre Legendre and Vladimir Makarenkov. Reconstruction of biogeographic and evolutionary networks using reticulograms. In Systematic Biology, Vol. 51(2):199-216, 2002.   Keywords: phylogenetic network, phylogeny, reconstruction, reticulogram. Note: http://www.labunix.uqam.ca/~makarenv/makarenv/Article_SB.pdf.         43 Mark T. Holder, Jennifer A. Anderson and Alisha K. Holloway. Difficulties in Detecting Hybridization. In Systematic Biology, Vol. 50(6):978-982, 2001.   Keywords: bootstrap, from rooted trees, hybridization, lateral gene transfer, lineage sorting, phylogenetic network, phylogeny, reconstruction, statistical model. Note: http://dx.doi.org/10.1080/106351501753462911.         Toggle abstract [No abstract available] 44 Alan R. Templeton, Keith A. Crandall and Charles F. Sing. A Cladistic Analysis of Phenotypic Associations With Haplotypes Inferred From Restriction Endonuclease Mapping and DNA Sequence Data. III. Cladogram Estimation. In GEN, Vol. 132:619-633, 2000.   Keywords: from sequences, parsimony, phylogenetic network, phylogeny, Program TCS, recombination, reconstruction, statistical parsimony. Note: http://www.genetics.org/cgi/content/abstract/132/2/619.         45 Tao Sang and Yang Zhong. Testing Hybridization Hypotheses Based on Incongruent Gene Trees. In Systematic Biology, Vol. 49(3):422-434, 2000.   Keywords: bootstrap, from rooted trees, hybridization, lateral gene transfer, lineage sorting, phylogenetic network, phylogeny, reconstruction, statistical model. Note: http://dx.doi.org/10.1080/10635159950127321.

46 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.         47 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.         48 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.         49 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.         50 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.         51 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.         52 Charles Semple. Size of a phylogenetic network. In DAM, Vol. 217(2):362-367, 2017.   Keywords: compressed network, Number of vertices, phylogenetic network, phylogeny. Note: http://www.math.canterbury.ac.nz/~c.semple/papers/S16.pdf.         53 Philippe Gambette, Katharina Huber and Steven Kelk. On the challenge of reconstructing level-1 phylogenetic networks from triplets and clusters. In JOMB, Vol. 74(7):1729-1751, 2017.   Keywords: galled tree, phylogenetic network, phylogeny, reconstruction, uniqueness. Note: http://dx.doi.org/10.1007/s00285-016-1068-3.         54 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.         55 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.         56 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.         57 Daniel H. Huson and Simone Linz. Autumn Algorithm - Computation of Hybridization Networks for Realistic Phylogenetic Trees. In TCBB, 2017.   Keywords: from rooted trees, phylogenetic network, phylogeny, Program Dendroscope, reconstruction. Note: https://simonelinz.files.wordpress.com/2016/06/hl16.pdf, to appear.         58 Misagh Kordi and Mukul S. Bansal. On the Complexity of Duplication-Transfer-Loss Reconciliation with Non-Binary Gene Trees. In TCBB, Vol. 14(3):587-599, 2017.   Keywords: duplication, from rooted trees, from species tree, lateral gene transfer, loss, NP complete, phylogenetic network, phylogeny, reconstruction. Note: http://compbio.engr.uconn.edu/papers/Kordi_DTLreconciliationPreprint2015.pdf.         59 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.         60 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.         61 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.         62 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.         63 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.         64 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.         65 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.         66 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.         67 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.         68 Jesper Jansson, Ramesh Rajaby and Wing-Kin Sung. An Efficient Algorithm for the Rooted Triplet Distance Between Galled Trees. In AlCoB17, Vol. 10252:115-126 of LNCS, Springer, 2017.   Keywords: distance between networks, from network, phylogenetic network, phylogeny, polynomial, reconstruction, triplet distance. Note: .         69 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.         70 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/.         71 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.         72 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.         73 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.         74 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.         75 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.         76 Jonathan Klawitter. The SNPR neighbourhood of tree-child networks. 2017.   Keywords: distance between networks, phylogenetic network, phylogeny, SPR distance, tree child network. Note: https://arxiv.org/abs/1707.09579         77 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.         78 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.         79 Ruzbeh Tusserkani, Hadi Poormohammadi, Azin Azadi and Changiz Eslahchi. Inferring phylogenies from minimal information. In AEEICB17, Pages 202-206, IEEE, 2017.   Keywords: from triplets, phylogenetic network, phylogeny, Program TripNet, reconstruction.         80 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.         81 Leo van Iersel and Vincent Moulton. Leaf-reconstructibility of phylogenetic networks. 2017.   Keywords: from network, level k phylogenetic network, phylogenetic network, phylogeny, reconstruction, uniqueness. Note: https://arxiv.org/abs/1701.08982.         82 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.         83 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.         84 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.         85 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.         86 Mohammad Hossein Reyhani and Hadi Poormohammadi. RPNCH: A Method for Constructing Rooted Phylogenetic Networks from Rooted Triplets based on Height Function. In Journal of Paramedical Sciences, Vol. 8(4):14-20, 2017.   Keywords: from triplets, heuristic, phylogenetic network, phylogeny, reconstruction. Note: http://journals.sbmu.ac.ir/jps/article/view/16707.         87 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.         88 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.         89 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.         90 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.         91 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.         92 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.         93 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.         94 Katharina Huber, Simone Linz, Vincent Moulton and Taoyang Wu. Spaces of phylogenetic networks from generalized nearest-neighbor interchange operations. In JOMB, Vol. 72(2):699-725, 2016.   Keywords: bound, distance between networks, from network, LST distance, phylogenetic network, phylogeny.         95 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.         96 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.         97 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.         98 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.         99 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 .         100 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.         101 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.         102 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.         103 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.         104 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.         105 Jonathan Mitchell. Distinguishing Convergence on Phylogenetic Networks. PhD thesis, University of Tasmania, Australia, 2016.   Keywords: phylogenetic network, phylogeny, statistical model. Note: http://arxiv.org/abs/1606.07160.         106 Rinku Mathur and Neeru Adlakha. A graph theoretic model for prediction of reticulation events and phylogenetic networks for DNA sequences. In Egyptian Journal of Basic and Applied Sciences, Vol. 3(3):263-271, 2016.   Keywords: from sequences, phylogenetic network, phylogeny, Program T REX. Note: http://dx.doi.org/10.1016/j.ejbas.2016.07.004.         107 Satyan L. Devadoss and Samantha Petti. A Space of Phylogenetic Networks. 2016.   Keywords: circular split system, phylogenetic network, phylogeny, split network. Note: http://arxiv.org/abs/1607.06978.         108 Andreas Gunawan, Bingxin Lu and Louxin Zhang. A program for verification of phylogenetic network models. In ECCB16, Vol. 32(17):i503-i510 of BIO, 2016.   Keywords: exponential algorithm, from network, from rooted trees, phylogenetic network, phylogeny, software, tree containment. Note: http://dx.doi.org/10.1093/bioinformatics/btw467.         109 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.         110 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.         111 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.         112 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.         113 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.         114 Katharina Huber, Vincent Moulton and Taoyang Wu. Transforming phylogenetic networks: Moving beyond tree space. In JTB, Vol. 404:30-39, 2016.   Keywords: distance between networks, level k phylogenetic network, phylogenetic network, phylogeny. Note: http://arxiv.org/abs/1601.01788.         115 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.         116 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.         117 Magnus Bordewich and Charles Semple. Determining phylogenetic networks from inter-taxa distances. In JOMB, Vol. 73(2):283-303, 2016.   Keywords: from distances, phylogenetic network, phylogeny, reconstruction, reticulation-visible network, time consistent network, tree child network, uniqueness. Note: http://132.181.26.35/~c.semple/papers/BS15b.pdf.         118 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.         119 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.         120 Juan Wang. A Metric on the Space of Partly Reduced Phylogenetic Networks. In BMRI, Vol. 2016(7534258):1-9, 2016.   Keywords: distance between networks, partly reduced networks, phylogenetic network, phylogeny, polynomial, reduced networks. Note: http://downloads.hindawi.com/journals/bmri/aip/7534258.pdf.         121 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.         122 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.         123 Juan Wang, Zhang Zhibin and Yanjuan Li. Constructing phylogenetic networks based on the isomorphism of datasets. In BMRI, Vol. 2016(4236858):1-7, 2016.   Keywords: from clusters, phylogenetic network, phylogeny, reconstruction. Note: http://downloads.hindawi.com/journals/bmri/aip/4236858.pdf.         124 Dan Graur. Reticulate evolution and phylogenetic networks. In Molecular and Genome Evolution, Chapter 6, Sinauer, 2016.   Keywords: phylogenetic network, phylogeny, survey. Note: http://www.sinauer.com/media/wysiwyg/samples/Graur_MGE1e_Ch06.pdf.         125 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/.         126 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.         127 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/.         128 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.         129 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.         130 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.         131 Andrew R. Francis and Mike Steel. Tree-like Reticulation Networks - When Do Tree-like Distances Also Support Reticulate Evolution? In MBIO, Vol. 259:12-19, 2015.   Keywords: from distances, phylogenetic network, phylogeny. Note: http://arxiv.org/abs/1405.2965.         132 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.         133 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.         134 Quan Nguyen. Likelihood-based Phylogenetic Network Inference by Approximate Structural Expectation Maximization. Master's thesis, University of Helsinki, 2015.   Keywords: BIC, likelihood, phylogenetic network, phylogeny, Program PhyloDAG, reconstruction, software. Note: http://urn.fi/URN:NBN:fi-fe2015062910525.         135 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.         136 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.         137 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.         138 Misagh Kordi and Mukul S. Bansal. On the Complexity of Duplication-Transfer-Loss Reconciliation with Non-Binary Gene Trees. In ISBRA15, Vol. 9096:187-198 of LNCS, springer, 2015.   Keywords: duplication, from rooted trees, from species tree, lateral gene transfer, loss, NP complete, phylogenetic network, phylogeny, reconstruction. Note: http://compbio.engr.uconn.edu/papers/Kordi_ISBRA2015.pdf.         139 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.         140 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.         141 Johannes Fischer and Daniel Peters. A Practical Succinct Data Structure for Tree-Like Graphs. In WALCOM15, Vol. 8973:65-76 of LNCS, springer, 2015.   Keywords: compression, from network, phylogenetic network, phylogeny.         142 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.         143 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.         144 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.         145 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.         146 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.         147 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.         148 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.         149 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.         150 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.         151 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.         152 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.         153 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.         154 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.         155 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.         156 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.         157 Leo van Iersel, Steven Kelk, Nela Lekic and Leen Stougie. Approximation algorithms for nonbinary agreement forests. In SIDMA, Vol. 28(1):49-66, 2014.   Keywords: agreement forest, approximation, from rooted trees, hybridization, minimum number, phylogenetic network, phylogeny, reconstruction. Note: http://arxiv.org/abs/1210.3211.         Toggle abstract "Given two rooted phylogenetic trees on the same set of taxa X, the Maximum Agreement Forest (maf) problem asks to find a forest that is, in a certain sense, common to both trees and has a minimum number of components. The Maximum Acyclic Agreement Forest (maaf) problem has the additional restriction that the components of the forest cannot have conflicting ancestral relations in the input trees. There has been considerable interest in the special cases of these problems in which the input trees are required to be binary. However, in practice, phylogenetic trees are rarely binary, due to uncertainty about the precise order of speciation events. Here, we show that the general, nonbinary version of maf has a polynomial-time 4-approximation and a fixedparameter tractable (exact) algorithm that runs in O(4opoly(n)) time, where n = |X| and k is the number of components of the agreement forest minus one. Moreover, we show that a c-approximation algorithm for nonbinary maf and a d-approximation algorithm for the classical problem Directed Feedback Vertex Set (dfvs) can be combined to yield a d(c+3)-approximation for nonbinary maaf. The algorithms for maf have been implemented and made publicly available. © 2014 Society for Industrial and Applied Mathematics." 158 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." 159 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." 160 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." 161 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.         162 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." 163 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." 164 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.         165 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.         166 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." 167 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." 168 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." 169 Ran Libeskind-Hadas, Yi-Chieh Wu, Mukul S. Bansal and Manolis Kellis. Pareto-optimal phylogenetic tree reconciliation. In ISMB14, Vol. 30:i87-i95 of BIO, 2014.   Keywords: duplication, lateral gene transfer, loss, phylogenetic network, phylogeny, polynomial, Program Xscape, reconstruction. Note: http://dx.doi.org/10.1093/bioinformatics/btu289.         Toggle abstract "Motivation: Phylogenetic tree reconciliation is a widely used method for reconstructing the evolutionary histories of gene families and species, hosts and parasites and other dependent pairs of entities. Reconciliation is typically performed using maximum parsimony, in which each evolutionary event type is assigned a cost and the objective is to find a reconciliation of minimum total cost. It is generally understood that reconciliations are sensitive to event costs, but little is understood about the relationship between event costs and solutions. Moreover, choosing appropriate event costs is a notoriously difficult problem. Results: We address this problem by giving an efficient algorithm for computing Pareto-optimal sets of reconciliations, thus providing the first systematic method for understanding the relationship between event costs and reconciliations. This, in turn, results in new techniques for computing event support values and, for cophylogenetic analyses, performing robust statistical tests. We provide new software tools and demonstrate their use on a number of datasets from evolutionary genomic and cophylogenetic studies. © 2014 The Author. Published by Oxford University Press. All rights reserved." 170 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." 171 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.         172 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.         173 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.         174 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.         175 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.         176 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.         177 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." 178 Benjamin Albrecht. Computing Hybridization Networks for Multiple Rooted Binary Phylogenetic Trees by Maximum Acyclic Agreement Forests. 2014.   Keywords: agreement forest, from rooted trees, minimum number, phylogenetic network, phylogeny, polynomial, Program Hybroscale, reconstruction. Note: http://arxiv.org/abs/1408.3044.         179 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.         180 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.         181 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." 182 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." 183 Paul Cordue, Simone Linz and Charles Semple. Phylogenetic Networks that Display a Tree Twice. In BMB, Vol. 76(10):2664-2679, 2014.   Keywords: from rooted trees, normal network, phylogenetic network, phylogeny, reconstruction, tree child network. Note: http://www.math.canterbury.ac.nz/~c.semple/papers/CLS14.pdf.         Toggle abstract "In the last decade, the use of phylogenetic networks to analyze the evolution of species whose past is likely to include reticulation events, such as horizontal gene transfer or hybridization, has gained popularity among evolutionary biologists. Nevertheless, the evolution of a particular gene can generally be described without reticulation events and therefore be represented by a phylogenetic tree. While this is not in contrast to each other, it places emphasis on the necessity of algorithms that analyze and summarize the tree-like information that is contained in a phylogenetic network. We contribute to the toolbox of such algorithms by investigating the question of whether or not a phylogenetic network embeds a tree twice and give a quadratic-time algorithm to solve this problem for a class of networks that is more general than tree-child networks. © 2014, Society for Mathematical Biology." 184 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.         185 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.         186 Yun Yu. Models and Methods for Evolutionary Histories Involving Hybridization and Incomplete Lineage Sorting. PhD thesis, Rice University, U.S.A., 2014.   Keywords: hybridization, incomplete lineage sorting, phylogenetic network, phylogeny, Program PhyloNet, reconstruction, software. Note: http://hdl.handle.net/1911/77583.         187 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.         188 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.         189 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.         190 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.         191 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." 192 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." 193 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." 194 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." 195 Teresa Piovesan and Steven Kelk. A simple fixed parameter tractable algorithm for computing the hybridization number of two (not necessarily binary) trees. In TCBB, Vol. 10(1):18-25, 2013.   Keywords: FPT, from rooted trees, phylogenetic network, phylogeny, Program TerminusEst, reconstruction. Note: http://arxiv.org/abs/1207.6090.         Toggle abstract "Here, we present a new fixed parameter tractable algorithm to compute the hybridization number (r) of two rooted, not necessarily binary phylogenetic trees on taxon set (X) in time ((6r r) · poly(n)), where (n= |X|). The novelty of this approach is its use of terminals, which are maximal elements of a natural partial order on (X), and several insights from the softwired clusters literature. This yields a surprisingly simple and practical bounded-search algorithm and offers an alternative perspective on the underlying combinatorial structure of the hybridization number problem. © 2004-2012 IEEE." 196 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." 197 Peter J. Humphries, Simone Linz and Charles Semple. On the complexity of computing the temporal hybridization number for two phylogenies. In DAM, Vol. 161:871-880, 2013.   Keywords: agreement forest, APX hard, characterization, from rooted trees, hybridization, NP complete, phylogenetic network, phylogeny, reconstruction, time consistent network. Note: http://ab.inf.uni-tuebingen.de/people/linz/publications/TAFapx.pdf.         Toggle abstract "Phylogenetic networks are now frequently used to explain the evolutionary history of a set of species for which a collection of gene trees, reconstructed from genetic material of different parts of the species' genomes, reveal inconsistencies. However, in the context of hybridization, the reconstructed networks are often not temporal. If a hybridization network is temporal, then it satisfies the time constraint of instantaneously occurring hybridization events; i.e. all species that are involved in such an event coexist in time. Furthermore, although a collection of phylogenetic trees can often be merged into a hybridization network that is temporal, many algorithms do not necessarily find such a network since their primary optimization objective is to minimize the number of hybridization events. In this paper, we present a characterization for when two rooted binary phylogenetic trees admit a temporal hybridization network. Furthermore, we show that the underlying optimization problem is APX-hard and, therefore, NP-hard. Thus, unless P=NP, it is unlikely that there are efficient algorithms for either computing an exact solution or approximating it within a ratio arbitrarily close to one. © 2012 Elsevier B.V. All rights reserved." 198 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." 199 Mukul S. Bansal, Eric J. Alm and Manolis Kellis. Reconciliation Revisited: Handling Multiple Optima when Reconciling with Duplication, Transfer, and Loss. In RECOMB13, Vol. 7821:1-13 of LNCS, springer, 2013.   Keywords: duplication, from rooted trees, from species tree, loss, phylogenetic network, phylogeny, polynomial, Program RANGER-DTL, reconstruction. Note: http://people.csail.mit.edu/mukul/Bansal_RECOMB2013.pdf.         Toggle abstract "Phylogenetic tree reconciliation is a powerful approach for inferring evolutionary events like gene duplication, horizontal gene transfer, and gene loss, which are fundamental to our understanding of molecular evolution. While Duplication-Loss (DL) reconciliation leads to a unique maximum-parsimony solution, Duplication-Transfer-Loss (DTL) reconciliation yields a multitude of optimal solutions, making it difficult the infer the true evolutionary history of the gene family. Here, we present an effective, efficient, and scalable method for dealing with this fundamental problem in DTL reconciliation. Our approach works by sampling the space of optimal reconciliations uniformly at random and aggregating the results. We present an algorithm to efficiently sample the space of optimal reconciliations uniformly at random in O(mn 2) time, where m and n denote the number of genes and species, respectively. We use these samples to understand how different optimal reconciliations vary in their node mapping and event assignments, and to investigate the impact of varying event costs. © 2013 Springer-Verlag." 200 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.         201 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.         202 Jialiang Yang, Stefan Grünewald and Xiu-Feng Wan. Quartet-Net: A Quartet Based Method to Reconstruct Phylogenetic Networks. In MBE, Vol. 30(5):1206-1217, 2013.   Keywords: from quartets, phylogenetic network, phylogeny, Program QuartetNet, reconstruction.         Toggle abstract "Phylogenetic networks can model reticulate evolutionary events such as hybridization, recombination, and horizontal gene transfer. However, reconstructing such networks is not trivial. Popular character-based methods are computationally inefficient, whereas distance-based methods cannot guarantee reconstruction accuracy because pairwise genetic distances only reflect partial information about a reticulate phylogeny. To balance accuracy and computational efficiency, here we introduce a quartet-based method to construct a phylogenetic network from a multiple sequence alignment. Unlike distances that only reflect the relationship between a pair of taxa, quartets contain information on the relationships among four taxa; these quartets provide adequate capacity to infer a more accurate phylogenetic network. In applications to simulated and biological data sets, we demonstrate that this novel method is robust and effective in reconstructing reticulate evolutionary events and it has the potential to infer more accurate phylogenetic distances than other conventional phylogenetic network construction methods such as Neighbor-Joining, Neighbor-Net, and Split Decomposition. This method can be used in constructing phylogenetic networks from simple evolutionary events involving a few reticulate events to complex evolutionary histories involving a large number of reticulate events. A software called Quartet-Net is implemented and available at http://sysbio.cvm.msstate.edu/QuartetNet/. © 2013 The Author." 203 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." 204 Hoa Vu, Francis Chin, Wing-Kai Hon, Henry Leung, Kunihiko Sadakane, Wing-Kin Sung and Siu-Ming Yiu. Reconstructing k-Reticulated Phylogenetic Network from a Set of Gene Trees. In ISBRA13, Vol. 7875:112-124 of LNCS, springer, 2013.   Keywords: from rooted trees, k-reticulated, phylogenetic network, phylogeny, polynomial, Program ARTNET, Program CMPT, reconstruction. Note: http://grid.cs.gsu.edu/~xguo9/publications/2013_Cloud%20computing%20for%20de%20novo%20metagenomic%20sequence%20assembly.pdf#page=123.         Toggle abstract "The time complexity of existing algorithms for reconstructing a level-x phylogenetic network increases exponentially in x. In this paper, we propose a new classification of phylogenetic networks called k-reticulated network. A k-reticulated network can model all level-k networks and some level-x networks with x > k. We design algorithms for reconstructing k-reticulated network (k = 1 or 2) with minimum number of hybrid nodes from a set of m binary trees, each with n leaves in O(mn 2) time. The implication is that some level-x networks with x > k can now be reconstructed in a faster way. We implemented our algorithm (ARTNET) and compared it with CMPT. We show that ARTNET outperforms CMPT in terms of running time and accuracy. We also consider the case when there does not exist a 2-reticulated network for the input trees. We present an algorithm computing a maximum subset of the species set so that a new set of subtrees can be combined into a 2-reticulated network. © 2013 Springer-Verlag." 205 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.         206 Simone Linz, Katherine St. John and Charles Semple. Counting trees in a phylogenetic network is #P-complete. In SICOMP, Vol. 42(4):1768-1776, 2013.   Keywords: counting, from network, phylogenetic network, phylogeny. Note: http://ab.inf.uni-tuebingen.de/people/linz/publications/counting.pdf.         207 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." 208 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." 209 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." 210 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." 211 Simone Linz. Reticulation. In Brenner's Encyclopedia of Genetics (Second Edition), 2013.   Keywords: phylogenetic network, phylogeny, survey.         212 Peter J. Humphries, Simone Linz and Charles Semple. Cherry picking: a characterization of the temporal hybridization number for a set of phylogenies. In BMB, Vol. 75(10):1879-1890, 2013.   Keywords: characterization, from rooted trees, hybridization, NP complete, phylogenetic network, phylogeny, reconstruction, time consistent network. Note: http://ab.inf.uni-tuebingen.de/people/linz/publications/CPSpaper.pdf.         Toggle abstract "Recently, we have shown that calculating the minimum-temporal-hybridization number for a set P of rooted binary phylogenetic trees is NP-hard and have characterized this minimum number when P consists of exactly two trees. In this paper, we give the first characterization of the problem for P being arbitrarily large. The characterization is in terms of cherries and the existence of a particular type of sequence. Furthermore, in an online appendix to the paper, we show that this new characterization can be used to show that computing the minimum-temporal hybridization number for two trees is fixed-parameter tractable. © 2013 Society for Mathematical Biology." 213 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.         214 Sha Zhu. Stochastic tree models and probabilistic modelling of gene trees of given species networks. PhD thesis, University of Canterbury, New Zealand, 2013.   Keywords: from network, generation, phylogenetic network, phylogeny, simulation, statistical model. Note: http://hdl.handle.net/10092/7944.         215 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." 216 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=.         217 Luay Nakhleh. Computational approaches to species phylogeny inference and gene tree reconciliation. In Trends in Ecology and Evolution, Vol. 28(12):719-728, 2013.   Keywords: from rooted trees, from species tree, phylogenetic network, phylogeny, reconstruction, survey. Note: http://bioinfo.cs.rice.edu/sites/bioinfo.cs.rice.edu/files/TREE-Nakhleh13.pdf.         Toggle abstract "An intricate relation exists between gene trees and species phylogenies, due to evolutionary processes that act on the genes within and across the branches of the species phylogeny. From an analytical perspective, gene trees serve as character states for inferring accurate species phylogenies, and species phylogenies serve as a backdrop against which gene trees are contrasted for elucidating evolutionary processes and parameters. In a 1997 paper, Maddison discussed this relation, reviewed the signatures left by three major evolutionary processes on the gene trees, and surveyed parsimony and likelihood criteria for utilizing these signatures to elucidate computationally this relation. Here, I review progress that has been made in developing computational methods for analyses under these two criteria, and survey remaining challenges. © 2013 Elsevier Ltd." 218 Thi-Hau Nguyen, Vincent Ranwez, Vincent Berry and Celine Scornavacca. Support Measures to Estimate the Reliability of Evolutionary Events Predicted by Reconciliation Methods. In PLoS ONE, Vol. 8(10):e73667, 2013.   Keywords: duplication, from rooted trees, from species tree, phylogenetic network, phylogeny, polynomial, Program GraphDTL, reconstruction. Note: http://dx.doi.org/10.1371/journal.pone.0073667.         Toggle abstract "The genome content of extant species is derived from that of ancestral genomes, distorted by evolutionary events such as gene duplications, transfers and losses. Reconciliation methods aim at recovering such events and at localizing them in the species history, by comparing gene family trees to species trees. These methods play an important role in studying genome evolution as well as in inferring orthology relationships. A major issue with reconciliation methods is that the reliability of predicted evolutionary events may be questioned for various reasons: Firstly, there may be multiple equally optimal reconciliations for a given species tree-gene tree pair. Secondly, reconciliation methods can be misled by inaccurate gene or species trees. Thirdly, predicted events may fluctuate with method parameters such as the cost or rate of elementary events. For all of these reasons, confidence values for predicted evolutionary events are sorely needed. It was recently suggested that the frequency of each event in the set of all optimal reconciliations could be used as a support measure. We put this proposition to the test here and also consider a variant where the support measure is obtained by additionally accounting for suboptimal reconciliations. Experiments on simulated data show the relevance of event supports computed by both methods, while resorting to suboptimal sampling was shown to be more effective. Unfortunately, we also show that, unlike the majority-rule consensus tree for phylogenies, there is no guarantee that a single reconciliation can contain all events having above 50% support. In this paper, we detail how to rely on the reconciliation graph to efficiently identify the median reconciliation. Such median reconciliation can be found in polynomial time within the potentially exponential set of most parsimonious reconciliations. © 2013 Nguyen et al." 219 Mukul S. Bansal, Eric J. Alm and Manolis Kellis. Reconciliation Revisited: Handling Multiple Optima when Reconciling with Duplication, Transfer, and Loss. In JCB, Vol. 20(10):738-754, 2013.   Keywords: duplication, from rooted trees, from species tree, loss, phylogenetic network, phylogeny, Program RANGER-DTL, reconstruction. Note: http://www.engr.uconn.edu/~mukul/Bansal_JCB2013.pdf.         Toggle abstract "Phylogenetic tree reconciliation is a powerful approach for inferring evolutionary events like gene duplication, horizontal gene transfer, and gene loss, which are fundamental to our understanding of molecular evolution. While duplication-loss (DL) reconciliation leads to a unique maximum-parsimony solution, duplication-transfer-loss (DTL) reconciliation yields a multitude of optimal solutions, making it difficult to infer the true evolutionary history of the gene family. This problem is further exacerbated by the fact that different event cost assignments yield different sets of optimal reconciliations. Here, we present an effective, efficient, and scalable method for dealing with these fundamental problems in DTL reconciliation. Our approach works by sampling the space of optimal reconciliations uniformly at random and aggregating the results. We show that even gene trees with only a few dozen genes often have millions of optimal reconciliations and present an algorithm to efficiently sample the space of optimal reconciliations uniformly at random in O(mn 2) time per sample, where m and n denote the number of genes and species, respectively. We use these samples to understand how different optimal reconciliations vary in their node mappings and event assignments and to investigate the impact of varying