Who is Who in Phylogenetic Networks

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1 R. A. Leo Elworth, Huw A. Ogilvie, Jiafan Zhu and Luay Nakhleh. Advances in Computational Methods for Phylogenetic Networks in the Presence of Hybridization. In Tandy Warnow editor, Bioinformatics and Phylogenetics. Seminal Contributions of Bernard Moret, Vol. 29 of Computational Biology, Springer, 2019.   Keywords: explicit network, phylogenetic network, phylogeny, Program Dendroscope, Program PhyloNet, Program PhyloNetworks SNaQ, Program PIRN, Program SplitsTree, reconstruction, survey. Note: https://bioinfocs.rice.edu/sites/g/files/bxs266/f/ElworthZhuOgilvieNakhleh.pdf         2 Louxin Zhang. Clusters, Trees, and Phylogenetic Network Classes. In Tandy Warnow editor, Bioinformatics and Phylogenetics. Seminal Contributions of Bernard Moret, Vol. 29:277-315 of Computational Biology, Springer, 2019.   Keywords: cluster containment, explicit network, phylogenetic network, phylogeny, polynomial, tree containment.         3 Gabriel Cardona, Joan Carles Pons and Celine Scornavacca. Generation of Binary Tree-Child phylogenetic networks. In PLoS Computational Biology, Vol. 15(10):e1007440.1-29, 2019.   Keywords: enumeration, explicit network, generation, phylogenetic network, phylogeny, Program PhyloNetwork, Program TCGenerators, software, tree-child network. Note: https://doi.org/10.1371/journal.pcbi.1007440.         4 Jiafan Zhu, Dingqiao Wen, Yun Yu, Heidi M. Meudt and Luay Nakhleh. Bayesian inference of phylogenetic networks from bi-allelic genetic markers. In PLoS Computational Biology, Vol. 14(1):e1005932.1-32, 2018.   Keywords: bayesian, explicit network, from multistate characters, phylogenetic network, phylogeny, Program PhyloNet. Note: https://doi.org/10.1371/journal.pcbi.1005932.         5 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, NNI moves, phylogenetic network, phylogeny, SPR distance. Note: https://hal-upec-upem.archives-ouvertes.fr/hal-01572624/en/.         6 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 subnetworks, from trinets, identifiability, phylogenetic network, phylogeny, reconstruction, uniqueness. Note: http://dx.doi.org/10.1093/sysbio/syu076.         7 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.         8 Fabio Pardi and Celine Scornavacca. Reconstructible Phylogenetic Networks: Do Not Distinguish the Indistinguishable. In PLoS Computational Biology, Vol. 11(4):e1007137.1-23, 2015.   Keywords: branch length, explicit network, from rooted trees, identifiability, phylogenetic network, phylogeny, reconstruction. Note: http://dx.doi.org/10.1371/journal.pcbi.1004135.         9 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." 10 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.         11 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." 12 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.         13 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.         14 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." 15 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.         16 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." 17 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)." 18 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)." 19 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.         20 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." 21 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." 22 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.         23 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):e1001010.1-13, 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." 24 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." 25 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." 26 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 sibling network, tree-child network. Note: http://books.google.fr/books?id=F4YIIUWb7yMC.         27 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.         28 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." 29 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." 30 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." 31 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." 32 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.         33 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.         34 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." 35 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.         36 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.         37 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." 38 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." 39 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." 40 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.         41 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.         42 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.         43 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.         44 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.         45 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.         46 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.         47 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] 48 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.         49 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.

50 Katharina Huber and Guillaume Scholz. Phylogenetic networks that are their own fold-ups. In AAM, Vol. 113(101959):1-24, 2020.   Keywords: characterization, explicit network, FU-stable network, phylogenetic network, phylogeny. Note: https://arxiv.org/abs/1804.01841.         51 Andrew R. Francis, Daniel H. Huson and Mike Steel. Normalising phylogenetic networks. 2020.   Keywords: explicit network, from network, normal network, phylogenetic network, phylogeny, polynomial, Program PhyloSketch, reconstruction, tree-child network. Note: https://arxiv.org/abs/2008.07797.         52 Gabriel Cardona and Louxin Zhang. Counting and Enumerating Tree-Child Networks and Their Subclasses. In JCSS, Vol. 114:84-104, 2020.   Keywords: counting, enumeration, explicit network, galled network, galled tree, normal network, phylogenetic network, phylogeny, tree-child network.         53 Michael Fuchs, Guan-Ru Yu and Louxin Zhang. On the Asymptotic Growth of the Number of Tree-Child Networks. 2020.   Keywords: counting, explicit network, phylogenetic network, phylogeny, tree-child network. Note: https://arxiv.org/abs/2003.08049.         54 Louxin Zhang. Recent Progresses in the Combinatorial and Algorithmic Study of Rooted Phylogenetic Networks. In WALCOM20, Vol. 12049:22-27 of LNCS, Springer, 2020.   Keywords: cluster containment, galled network, galled tree, nearly-stable network, phylogenetic network, phylogeny, polynomial, reticulation-visible network, survey, time consistent network, tree containment, tree-based network, tree-child network.         55 Andreas Gunawan, Jeyaram Rathin and Louxin Zhang. Counting and enumerating galled networks. In DAM, Vol. 283:644-654, 2020.   Keywords: counting, enumeration, explicit network, galled network, phylogenetic network, phylogeny. Note: https://arxiv.org/abs/1812.08569.         56 Marefatollah Mansouri. Counting General Phylogenetic networks. 2020.   Keywords: counting, explicit network, phylogenetic network, phylogeny. Note: https://arxiv.org/abs/2005.14547.         57 Marefatollah Mansouri. Combinatorial properties of phylogenetic networks. PhD thesis, Vienna University of Technology (Austria), Institute of Discrete Mathematics and Geometry, 2020.   Keywords: counting, explicit network, galled tree, level k phylogenetic network, normal network, phylogenetic network, phylogeny. Note: https://dmg.tuwien.ac.at/bgitten/Theses/mansouri.pdf.         58 Mathilde Bouvel, Philippe Gambette and Marefatollah Mansouri. Counting Phylogenetic Networks of Level 1 and 2. In JOMB, 2020.   Keywords: counting, explicit network, level k phylogenetic network, phylogenetic network, phylogeny. Note: https://arxiv.org/abs/1909.10460, to appear.         59 Jonathan Klawitter and Peter Stumpf. Drawing Tree-Based Phylogenetic Networks with Minimum Number of Crossings. 2020.   Keywords: explicit network, FPT, minimum number, NP complete, phylogenetic network, phylogeny, polynomial, visualization. Note: https://arxiv.org/abs/2008.08960.         60 Elizabeth Gross, Leo van Iersel, Remie Janssen, Mark Jones, Colby Long and Yukihiro Murakami. Distinguishing level-1 phylogenetic networks on the basis of data generated by Markov processes. 2020.   Keywords: characterization, distinguishability, explicit network, galled tree, phylogenetic network, population genetics, semidirected network, statistical model, uniqueness. Note: https://arxiv.org/abs/2007.08782.         61 Remie Janssen, Mark Jones and Yukihiro Murakami. Combining Networks Using Cherry Picking Sequences. In AlCoB20, Vol. 12099:77-92 of LNCS, Springer, 2020.   Keywords: cherry-picking, explicit network, FPT, from network, hybridization, orchard network, phylogenetic network, phylogeny, tree-child network.         62 Hannah Brown, Lei Zuo and Dan Gusfield. Comparing Integer Linear Programming to SAT-Solving for Hard Problems in Computational and Systems Biology. In AlCoB2020, Vol. 12099:63-76 of LNCS, Springer, 2020.   Keywords: from binary characters, History bound, integer linear programming, minimum number, phylogeny, SAT. Note: https://doi.org/10.1007/978-3-030-42266-0_6.         63 Remie Janssen and Yukihiro Murakami. Linear Time Algorithm for Tree-Child Network Containment. In AlCoB20, Vol. 12099:93-107 of LNCS, Springer, 2020.   Keywords: explicit network, from network, isomorphism, phylogenetic network, phylogeny, polynomial, reconstruction, tree-child network, tree-child sequence. Note: https://doi.org/10.1007/978-3-030-42266-0_8.         64 Leo van Iersel, Remie Janssen, Mark Jones, Yukihiro Murakami and Norbert Zeh. Polynomial-Time Algorithms for Phylogenetic Inference Problems Involving Duplication and Reticulation. In TCBB, Vol. 17(1):14-26, 2020.   Keywords: hybridization, minimum number, parental hybridization, phylogenetic network, phylogeny, reconstruction, weakly displaying. Note: http://pure.tudelft.nl/ws/portalfiles/portal/71270795/08798653.pdf.         65 Momoko Hayamizu, Katharina Huber, Vincent Moulton and Yukihiro Murakami. Recognizing and realizing cactus metrics. In IPL, Vol. 157(105916):1-5, 2020.   Keywords: cactus graph, from distances, level k phylogenetic network, optimal realization, polynomial. Note: https://doi.org/10.1016/j.ipl.2020.105916.         66 Leo van Iersel, Vincent Moulton and Yukihiro Murakami. Reconstructibility of unrooted level-k phylogenetic networks from distances. In AAM, Vol. 120(102075):1-30, 2020.   Keywords: from distances, galled tree, level k phylogenetic network, phylogenetic network, phylogeny, reconstruction, uniqueness. Note: https://doi.org/10.1016/j.aam.2020.102075.         67 Jonathan Klawitter. The agreement distance of unrooted phylogenetic networks. In DMTCS, Vol. 21(2):22.1-23, 2020.   Keywords: agreement forest, distance between networks, explicit network, from network, phylogenetic network, phylogeny. Note: https://dmtcs.episciences.org/6567/pdf.         68 Stefan Forcey and Drew Scalzo. Phylogenetic networks as circuits with resistance distance. 2020.   Keywords: circular split system, from distances, level k phylogenetic network, NeighborNet, nested network, phylogenetic network, phylogeny, split network. Note: https://arxiv.org/abs/2007.13574.         69 Cassandra Durell and Stefan Forcey. Level-1 phylogenetic networks and their balanced minimum evolution polytopes. In JOMB, Vol. 80:1235-1263, 2020.   Keywords: from distances, galled tree, phylogenetic network, phylogeny, reconstruction, split network. Note: https://arxiv.org/pdf/1905.09160.pdf.         70 Simone Linz and Charles Semple. Caterpillars on three and four leaves are sufficient to reconstruct binary normal networks. In JOMB, 2020.   Keywords: explicit network, from rooted trees, from triplets, normal network, phylogenetic network, phylogeny, reconstruction, uniqueness. Note: https://arxiv.org/abs/2002.00483, to appear.         71 Hadi Poormohammadi and Mohsen Sardari Zarchi. Netcombin: An algorithm for constructing optimal phylogenetic network from rooted triplets. In PLoS ONE, Vol. 15(9):e0227842.1-25, 2020.   Keywords: explicit network, from triplets, heuristic, phylogenetic network, phylogeny, Program Simplistic, Program TripNet, reconstruction. Note: https://doi.org/10.1371/journal.pone.0227842.         72 Hadi Poormohammadi, Mohsen Sardari Zarchi and Hossein Ghaneai. NCHB: A method for constructing rooted phylogenetic networks from rooted triplets based on height function and binarization. In JTB, Vol. 489(110144), 2020.   Keywords: explicit network, from triplets, heuristic, phylogenetic network, phylogeny, Program Simplistic, Program TripNet, reconstruction. Note: https://doi.org/10.1016/j.jtbi.2019.110144.         73 Katharina Huber, Simone Linz and Vincent Moulton. Weakly displaying trees in temporal tree-child network. 2020.   Keywords: cherry-picking, from rooted trees, phylogenetic network, phylogeny, reconstruction, rigidly displaying, time consistent network, tree-child network, weakly displaying. Note: https://arxiv.org/abs/2004.02634.         74 Joan Carles Pons, Celine Scornavacca and Gabriel Cardona. Generation of Level-k LGT Networks. In TCBB, Vol. 17(1):158-164, 2020.   Keywords: explicit network, level k phylogenetic network, LGT network, phylogenetic network, phylogeny.         75 Joan Carles Pons, Charles Semple and Mike Steel. Tree-based networks: characterisations, metrics, and support trees. In JOMB, Vol. 78(4):899-918, 2019.   Keywords: characterization, explicit network, from network, phylogenetic network, phylogeny, time consistent network, tree-based network. Note: https://arxiv.org/abs/1710.07836.         76 Katharina Huber, Vincent Moulton and Taoyang Wu. Hierarchies from lowest stable ancestors in nonbinary phylogenetic networks. In JOC, Vol. 36:200-231, 2019.   Keywords: characterization, explicit network, phylogenetic network, phylogeny. Note: https://link.springer.com/content/pdf/10.1007/s00357-018-9279-5.pdf.         77 Simone Linz and Charles Semple. Attaching leaves and picking cherries to characterise the hybridisation number for a set of phylogenies. In AAM, Vol. 105:102-129, 2019.   Keywords: agreement forest, cherry-picking, explicit network, from rooted trees, phylogenetic network, phylogeny, reconstruction, tree-child network. Note: https://doi.org/10.1016/j.aam.2019.01.004.         78 Jonathan Klawitter. The agreement distance of rooted phylogenetic networks. In DMTCS, Vol. 21(3):19.1-24, 2019.   Keywords: agreement forest, distance between networks, explicit network, from network, phylogenetic network, phylogeny, SPR distance. Note: https://arxiv.org/abs/1806.05800.         79 Janosch Döcker, Leo van Iersel, Steven Kelk and Simone Linz. Deciding the existence of a cherry-picking sequence is hard on two trees. In DAM, Vol. 260:131-143, 2019.   Keywords: cherry-picking, explicit network, hybridization, minimum number, NP complete, phylogenetic network, phylogeny, reconstruction, temporal-hybridization number, time consistent network, tree-child network. Note: https://arxiv.org/abs/1712.02965.         80 Jonathan Klawitter and Simone Linz. On the Subnet Prune and Regraft Distance. In ELJC, Vol. 26(2):P2.3.1-23, 2019.   Keywords: agreement forest, explicit network, phylogenetic network, phylogeny, reticulation-visible network, SPR distance, tree-based network, tree-child network. Note: https://arxiv.org/abs/1805.07839.         81 Michael Fuchs, Bernhard Gittenberger and Marefatollah Mansouri. Counting Phylogenetic Networks with Few Reticulation Vertices: Tree-Child and Normal Networks. In Australasian Journal of Combinatorics, Vol. 73(2):385-423, 2019.   Keywords: counting, explicit network, normal network, phylogenetic network, phylogeny. Note: https://arxiv.org/abs/1803.11325, see also erratum at https://arxiv.org/abs/2006.15784.         82 Andreas Gunawan, Hongwei Yan and Louxin Zhang. Compression of Phylogenetic Networks and Algorithm for the Tree Containment Problem. In JCB, Vol. 25(3), 2019.   Keywords: explicit network, phylogenetic network, phylogeny, polynomial, quasi-reticulation-visible network, reticulation-visible network, tree containment, tree-child network. Note: https://arxiv.org/abs/1806.07625.         83 Louxin Zhang. Generating normal networks via leaf insertion and nearest neighbor interchange. In BMC Bioinformatics, Vol. 20(642):1-9, 2019.   Keywords: enumeration, explicit network, generation, NNI moves, phylogenetic network, phylogeny. Note: https://link.springer.com/content/pdf/10.1186/s12859-019-3209-3.pdf.         84 Juan Wang and Maozu Guo. IGNet: Constructing Rooted Phylogenetic Networks Based on Incompatible Graphs. In ICNC-FSKD19, Vol. 1075:894-900 of Advances in Intelligent Systems and Computing, Springer, 2019.   Keywords: explicit network, from rooted trees, phylogenetic network, phylogeny, Program BIMLR, Program IGNet, Program LNetwork, reconstruction, software.         85 Yukihiro Murakami, Leo van Iersel, Remie Janssen, Mark Jones and Vincent Moulton. Reconstructing Tree-Child Networks from Reticulate-Edge-Deleted Subnetworks. In BMB, Vol. 81:3823-3863, 2019.   Keywords: from subnetworks, level k phylogenetic network, phylogenetic network, phylogeny, reconstruction, tree-child network, uniqueness, valid network. Note: https://doi.org/10.1007/s11538-019-00641-w.         86 Yan Hong and Juan Wang. Frin: An Efficient Method for Representing Genome Evolutionary History. In Frontiers in Genetics, Vol. 10(1261):1-8, 2019.   Keywords: explicit network, from clusters, phylogenetic network, phylogeny, Program Frin, reconstruction. Note: https://doi.org/10.3389/fgene.2019.01261.         87 Juan Wang and Maozu Guo. A review of metrics measuring dissimilarity for rooted phylogenetic networks. In Briefings in Bioinformatics, Vol. 20(6):1972-1980, 2019.   Keywords: distance between networks, explicit network, from network, mu distance, phylogenetic network, phylogeny, survey, tree sibling network, tree-child network.         88 Christopher Blair and Cécile Ané. Phylogenetic trees and networks can serve as powerful and complementary approaches for analysis of genomic data. In SB, Vol. 69(3):593-601, 2019.   Keywords: likelihood, phylogenetic network, phylogeny, Program PhyloNetwork, Program PhyloNetworks SNaQ, survey.         89 Péter L. Erdös, Leo van Iersel and Mark Jones. Not all phylogenetic networks are leaf-reconstructible. In JOMB, Vol. 79(5):1623-1638, 2019.   Keywords: from subnetworks, phylogenetic network, phylogeny, reconstruction, uniqueness. Note: https://doi.org/10.1007/s00285-019-01405-9.         90 Konstantinos Mampentzidis. Comparison and Construction of Phylogenetic Trees and Networks. PhD thesis, Aarhus University, Denmark, 2019.   Keywords: distance between networks, explicit network, from network, phylogenetic network, phylogeny, polynomial, triplet distance. Note: https://pure.au.dk/ws/files/172250681/thesis_Konstantinos_Mampentzidis.pdf.         91 Jesper Jansson, Konstantinos Mampentzidis, Ramesh Rajaby and Wing-Kin Sung. Computing the Rooted Triplet Distance Between Phylogenetic Networks. In IWOCA19, Vol. 11638:290-303 of LNCS, Springer, 2019.   Keywords: distance between networks, from network, phylogenetic network, phylogeny, polynomial, triplet distance.         92 Janosch Döcker, Simone Linz and Charles Semple. Displaying trees across two phylogenetic networks. In TCS, Vol. 796:129-146, 2019.   Keywords: display set, explicit network, normal network, phylogenetic network, phylogeny, time consistent network, tree-child network. Note: https://arxiv.org/abs/1901.06612.         93 Katharina Huber, Leo van Iersel, Remie Janssen, Mark Jones, Vincent Moulton, Yukihiro Murakami and Charles Semple. Rooting for phylogenetic networks. 2019.   Keywords: explicit network, from network, level k phylogenetic network, orchard network, orientation, phylogenetic network, phylogeny, reconstruction, stack-free network, tree-based network, tree-child network, valid network. Note: https://arxiv.org/abs/1906.07430.         94 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, Vol. 80(11):2993-3022, 2018.   Keywords: explicit network, FPT, from network, from unrooted trees, NP complete, phylogenetic network, phylogeny, reconstruction, tree containment. Note: https://hal.inria.fr/hal-01599716.         95 Laura Jetten and Leo van Iersel. Nonbinary tree-based phylogenetic networks. In TCBB, Vol. 15(1):205-217, 2018.   Keywords: characterization, explicit network, phylogenetic network, phylogeny, tree-based network. Note: http://arxiv.org/abs/1601.04974.         96 Daniel H. Huson and Simone Linz. Autumn Algorithm - Computation of Hybridization Networks for Realistic Phylogenetic Trees. In TCBB, Vol. 15:398-410, 2018.   Keywords: explicit network, from rooted trees, phylogenetic network, phylogeny, Program Dendroscope, reconstruction. Note: https://simonelinz.files.wordpress.com/2016/06/hl16.pdf.         97 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.         98 Mathias Weller. Linear-Time Tree Containment in Phylogenetic Networks. In RECOMB-CG18, Vol. 11183:309-323 of LNCS, Springer, 2018.   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.         99 Andrew R. Francis, Katharina Huber, Vincent Moulton and Taoyang Wu. Bounds for phylogenetic network space metrics. In JOMB, Vol. 76(5):1229-1248, 2018.   Keywords: bound, distance between networks, from network, NNI distance, NNI moves, phylogenetic network, phylogeny, SPR distance, TBR distance. Note: https://arxiv.org/abs/1702.05609.         100 Hussein A. Hejase, Natalie VandePol, Gregory A. Bonito and Kevin J. Liu. Fast and accurate statistical inference of phylogenetic networks using large-scale genomic sequence data. In RECOMB-CG18, Vol. 11183:242-259 of LNCS, Springer, 2018.   Keywords: explicit network, from rooted trees, heuristic, phylogenetic network, phylogeny, Program FastNet, reconstruction. Note: http://biorxiv.org/content/early/2017/05/01/132795.         101 Andrew R. Francis, Katharina Huber and Vincent Moulton. Tree-based unrooted phylogenetic networks. In BMB, Vol. 80(2):404-416, 2018.   Keywords: characterization, explicit network, NP complete, phylogenetic network, phylogeny, tree containment, tree-based network, unrooted tree-based network. Note: https://arxiv.org/abs/1704.02062.         102 Magnus Bordewich, Charles Semple and Nihan Tokac. Constructing tree-child networks from distance matrices. In Algorithmica, Vol. 80(8):2240-2259, 2018.   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.         103 Andreas Gunawan. Solving the Tree Containment Problem for Reticulation-visible Networks in Linear Time. In AlCoB18, Vol. 10849:24-36 of LNCS, Springer, 2018.   Keywords: explicit network, from network, from rooted trees, phylogenetic network, phylogeny, polynomial, reticulation-visible network, tree containment. Note: https://arxiv.org/abs/1702.04088.         104 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, Vol. 246:62-79, 2018.   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/.         105 Remie Janssen, Mark Jones, Péter L. Erdös, Leo van Iersel and Celine Scornavacca. Exploring the tiers of rooted phylogenetic network space using tail moves. In BMB, Vol. 80(8):2177-2208, 2018.   Keywords: distance between networks, explicit network, from network, NNI moves, orientation, phylogenetic network, phylogeny, SPR distance. Note: https://arxiv.org/abs/1708.07656.         106 Jonathan Klawitter. The SNPR neighbourhood of tree-child networks. In JGAA, Vol. 22(2):329-355, 2018.   Keywords: distance between networks, phylogenetic network, phylogeny, SPR distance, tree-child network. 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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.         132 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.         133 Satyan L. Devadoss and Samantha Petti. A Space of Phylogenetic Networks. In SIAM Journal on Applied Algebra and Geometry, Vol. 1(1):683-705, 2017.   Keywords: abstract network, circular split system, phylogenetic network, phylogeny, split network. Note: http://arxiv.org/abs/1607.06978.         134 Charles Semple. Size of a phylogenetic network. 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Note: http://arxiv.org/abs/1511.08387.         137 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.         138 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.         139 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.         140 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.         141 Gabriel Cardona and Joan Carles Pons. Reconstruction of LGT networks from tri-LGT-nets. 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In AlCoB17, Vol. 10252:115-126 of LNCS, Springer, 2017.   Keywords: distance between networks, from network, phylogenetic network, phylogeny, polynomial, reconstruction, triplet distance. Note: .         147 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, from subnetworks, galled tree, level k phylogenetic network, NP complete, phylogenetic network, phylogeny, reconstruction. Note: http://dx.doi.org/10.1007/s11538-017-0275-4.         148 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. 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In AEEICB17, Pages 202-206, IEEE, 2017.   Keywords: from triplets, phylogenetic network, phylogeny, Program TripNet, reconstruction.         152 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.         153 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.         154 Mohammad Hossein Reyhani and Hadi Poormohammadi. RPNCH: A Method for Constructing Rooted Phylogenetic Networks from Rooted Triplets based on Height Function. In Archives of Advances in Biosciences, Vol. 8(4):14-20, 2017.   Keywords: explicit network, from triplets, heuristic, phylogenetic network, phylogeny, reconstruction. Note: http://journals.sbmu.ac.ir/jps/article/view/16707.         155 Hussein A. Hejase. Scalable Phylogenetic Analysis and Functional Interpretation of Genomes with Complex Evolutionary Histories. PhD thesis, Michigan State University, 2017.   Keywords: explicit network, from rooted trees, heuristic, phylogenetic network, phylogeny, Program FastNet, reconstruction. Note: https://dx.doi.org/10.25335/M5T855.         156 Edwin Jacox, Mathias Weller, Eric Tannier and Celine Scornavacca. Resolution and reconciliation of non-binary gene trees with transfers, duplications and losses. In BIO, Vol. 33(7):980-987, 2017.   Keywords: duplication, explicit network, FPT, from rooted trees, from species tree, lateral gene transfer, loss, phylogenetic network, phylogeny, reconstruction. Note: http://dx.doi.org/10.1093/bioinformatics/btw778.         157 Luay Nakhleh. Phylogenetic Networks: From Displayed Trees to a Distribution of Gene Trees. Phyloseminar #70, 2017.   Keywords: bayesian, coalescent, explicit network, phylogenetic network, phylogeny, Program PhyloNet, reconstruction, statistical model. Note: https://www.youtube.com/watch?v=dkQsvLUUDcQ.         158 Celine Scornavacca. Occam's razor in phylogenetic network reconstruction. Phyloseminar #71, 2017.   Keywords: explicit network, from rooted trees, parsimony, phylogenetic network, phylogeny, reconstruction. Note: https://www.youtube.com/watch?v=W6tEVulgQu8.         159 Cécile Ané. From reconstructing to using phylogenetic networks. Phyloseminar #72, 2017.   Keywords: explicit network, from sequences, likelihood, phylogenetic network, phylogeny, Program PhyloNetworks SNaQ, reconstruction, semidirected network. Note: https://www.youtube.com/watch?v=PF4j_JOQP0c.         160 Paul Bastide. Shifted stochastic processes evolving on trees : application to models of adaptive evolution on phylogenies. PhD thesis, Université Paris Saclay, 2017.   Keywords: ancestral trait reconstruction, bayesian, explicit network, phylogenetic network, phylogeny, Program PhyloNetworks SNaQ, reconstruction, statistical model. Note: https://tel.archives-ouvertes.fr/tel-01629648/en/, slides..         161 Kuang-Yu Chang, Yun Cui, Siu-Ming Yiu and Wing-Kai Hon. Reconstructing One-Articulated Networks with Distance Matrices. In ISBRA17, Vol. 10330:34-45 of LNCS, Springer, 2017.   Keywords: explicit network, from distances, k-reticulated, phylogenetic network, phylogeny, reconstruction. Note: https://link.springer.com/content/pdf/10.1007%2F978-3-319-59575-7.pdf#page=100.         162 Dingqiao Wen. Bayesian Inference of Phylogenetic Networks from Sequence Data. PhD thesis, Rice University, 2017.   Keywords: bayesian, explicit network, phylogenetic network, phylogeny, reconstruction.         163 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.         164 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.         165 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.         166 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.         167 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. 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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 .         171 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.         172 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.         173 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.         174 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.         175 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.         176 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.         177 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. 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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.         181 Nikita Alexeev and Max A. Alekseyev. Combinatorial Scoring of Phylogenetic Networks. In COCOON16, Vol. 9797:560-572 of LNCS, Springer, 2016.   Keywords: cactus graph, counting, explicit network, galled tree, phylogenetic network, phylogeny. Note: http://arxiv.org/abs/1602.02841.         182 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-based network, tree-child network. 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In JTB, Vol. 396:204-206, 2016.   Keywords: explicit network, phylogenetic network, phylogeny, tree-based network. Note: http://arxiv.org/abs/1512.02402.         186 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.         187 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 subnetworks, from trinets, galled tree, phylogenetic network, phylogeny, Program LEV1ATHAN, Program TriLoNet, reconstruction.         188 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.         189 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.         190 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, incomplete lineage sorting, phylogenetic network, phylogeny, statistical model, tree-based network, weakly displaying. 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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/.         195 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.         196 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/.         197 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.         198 Kristina Wicke. Extending the concept of phylogenetic diversity and its measures from trees to networks. Master's thesis, Ernst-Moritz-Arndt-Universität Greifswald, 2016.   Keywords: diversity, explicit network, from network, normal network, phylogenetic network, phylogeny. Note: https://math-inf.uni-greifswald.de/fileadmin/uni-greifswald/fakultaet/mnf/mathinf/wicke/MasterThesis_KristinaWicke.pdf.         199 Edwin Jacox, Cédric Chauve, Gergely J. Szöllösi, Yann Ponty and Celine Scornavacca. EcceTERA: comprehensive gene tree-species tree reconciliation using parsimony. In BIO, Vol. 32(13):2056-2058, 2016.   Keywords: duplication, explicit network, from rooted trees, from species tree, lateral gene transfer, loss, parsimony, phylogenetic network, phylogeny, polynomial, Program ecceTERA. Note: https://doi.org/10.1093/bioinformatics/btw105.         200 Pei Wu. Quartet weights in phylogenetic network reconstruction. PhD thesis, University of Chinese Academy of Sciences, 2016.   Keywords: abstract network, from distances, from quartets, phylogenetic network, phylogeny, reconstruction, split, split network. Note: https://www.researchgate.net/publication/324475948_Quartet_weights_in_phylogenetic_network_reconstruction.         201 Monika Balvociute. Flat Embeddings of Genetic and Distance Data. PhD thesis, University of Otago, 2016.   Keywords: abstract network, flat, phylogenetic network, phylogeny, planar, Program FlatNJ, Program SplitsTree, split, split network. Note: http://hdl.handle.net/10523/6286.         202 Dingqiao Wen. Bayesian Inference of Phylogenetic Networks. Master's thesis, Rice University, Texas, 2016.   Keywords: bayesian, explicit network, phylogenetic network, phylogeny, Program PhyloNet, reconstruction. Note: https://scholarship.rice.edu/bitstream/handle/1911/96515/WEN-DOCUMENT-2016.pdf?sequence=1&isAllowed=y.         203 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.         204 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.         205 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.         206 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.         207 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.         208 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.         209 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.         210 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.         211 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.         212 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.         213 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.         214 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.         215 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.         216 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.         217 Maxime Morgado. Propriétés structurelles et relations des classes de réseaux phylogénétiques. Master's thesis, ENS Cachan, 2015.   Keywords: compressed network, distinct-cluster network, explicit network, galled network, galled tree, level k phylogenetic network, nested network, normal network, phylogenetic network, phylogeny, regular network, spread, tree containment, tree sibling network, tree-based network, tree-child network, unicyclic network.         218 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.         219 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.         220 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.         221 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.         222 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.         223 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.         224 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.         225 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.         226 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.         227 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.         228 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.         229 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.         230 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.         231 Claudia Solís-Lemus. Statistical methods to infer population structure with coalescence and gene flow. PhD thesis, University of Wisconsin-Madison, 2015.   Keywords: explicit network,