Who is Who in Phylogenetic Networks

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1 D. S. Rao, G. N. Kumar, Dheeresh K. Mallick and Prasanta K. Jana. Parallel Construction of Conflict Graph for Phylogenetic Network Problem. In Pattern Recognition and Machine Intelligence (PReMI'07), Vol. 4815:398-405 of LNCS, springer, 2007.   Note: http://dx.doi.org/10.1007/978-3-540-77046-6_49.

2 Gergely J. Szöllösi and Vincent Daubin. Modeling Gene Family Evolution and Reconciling Phylogenetic Discord. In Evolutionary Genomics, Statistical and Computational Methods, Volume 2, Methods in Molecular Biology, Vol. 856:29-51, Chapter 2, springer, 2011.   Keywords: duplication, from multilabeled tree, lateral gene transfer, likelihood, phylogeny, reconstruction, statistical model. Note: ArXiv version entitled The pattern and process of gene family evolution.         Toggle abstract "Large-scale databases are available that contain homologous gene families constructed from hundreds of complete genome sequences from across the three domains of life. Here, we discuss the approaches of increasing complexity aimed at extracting information on the pattern and process of gene family evolution from such datasets. In particular, we consider the models that invoke processes of gene birth (duplication and transfer) and death (loss) to explain the evolution of gene families. First, we review birth-and-death models of family size evolution and their implications in light of the universal features of family size distribution observed across different species and the three domains of life. Subsequently, we proceed to recent developments on models capable of more completely considering information in the sequences of homologous gene families through the probabilistic reconciliation of the phylogenetic histories of individual genes with the phylogenetic history of the genomes in which they have resided. To illustrate the methods and results presented, we use data from the HOGENOM database, demonstrating that the distribution of homologous gene family sizes in the genomes of the eukaryota, archaea, and bacteria exhibits remarkably similar shapes. We show that these distributions are best described by models of gene family size evolution, where for individual genes the death (loss) rate is larger than the birth (duplication and transfer) rate but new families are continually supplied to the genome by a process of origination. Finally, we use probabilistic reconciliation methods to take into consideration additional information from gene phylogenies, and find that, for prokaryotes, the majority of birth events are the result of transfer. © 2012 Springer Science+Business Media, LLC." 3 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.         4 Jesper Jansson and Wing-Kin Sung. Inferring a level-1 phylogenetic network from a dense set of rooted triplets. In TCS, Vol. 363(1):60-68, 2006. 1 comment   Keywords: explicit network, from triplets, galled tree, level k phylogenetic network, phylogenetic network, phylogeny, polynomial, reconstruction. Note: http://www.df.lth.se/~jj/Publications/ipnrt8_TCS2006.pdf.         Toggle abstract "We consider the following problem: Given a set T of rooted triplets with leaf set L, determine whether there exists a phylogenetic network consistent with T, and if so, construct one. We show that if no restrictions are placed on the hybrid nodes in the solution, the problem is trivially solved in polynomial time by a simple sorting network-based construction. For the more interesting (and biologically more motivated) case where the solution is required to be a level-1 phylogenetic network, we present an algorithm solving the problem in O (| T |2) time when T is dense, i.e., when T contains at least one rooted triplet for each cardinality three subset of L. We also give an O (| T |5 / 3)-time algorithm for finding the set of all phylogenetic networks having a single hybrid node attached to exactly one leaf (and having no other hybrid nodes) that are consistent with a given dense set of rooted triplets. © 2006 Elsevier B.V. All rights reserved." 5 Mohd Abdul Hai Zahid, Ankush Mittal and Ramesh C. Joshi. A pattern recognition-based approach for phylogenetic network construction with constrained recombination. In Pattern Recognition, Vol. 39:2312-2322, 2006.   Note: http://www.isical.ac.in/~zahid_t/publications/papers/revision 2.pdf.         6 Sergey Bereg and Kathryn Bean. Constructing Phylogenetic Networks from Trees. In BIBE05, Pages 299-305, 2005. 1 comment   Keywords: evaluation, from distances, phylogenetic network, phylogeny, Program SplitsTree, Program T REX, reconstruction, split, split network. Note: http://dx.doi.org/10.1109/BIBE.2005.19.         Toggle abstract We present a new method of constructing a phylogenetic network from a given phylogenetic tree. It is based on a procedure that locally improves the tree. The procedure is quite general and can be applied to phylogenetic networks. By repeating local improvements user can introduce a given number of recombination cycles. A sequence of networks with decreasing distance deviation can be generated. The algorithm is efficient and shows a good performance on an example with plants. This is due to the fact that the update in every step is local and optimal. © 2005 IEEE. 7 Jesper Jansson and Wing-Kin Sung. Inferring a level-1 phylogenetic network from a dense set of rooted triplets. In COCOON04, Vol. 3106:462-471 of LNCS, springer, 2004. 1 comment   Keywords: explicit network, from triplets, galled tree, level k phylogenetic network, phylogenetic network, phylogeny, polynomial, reconstruction. Note: http://www.df.lth.se/~jj/Publications/ipnrt6_COCOON2004.pdf.         8 C. Randal Linder and Loren H. Rieseberg. Reconstructing patterns of reticulate evolution in plants. In American Journal of Botany, Vol. 91(10):1700-1708, 2004.   Keywords: distance between networks, hybridization, phylogenetic network, phylogeny, reconstruction, survey, tripartition distance. Note: http://www.amjbot.org/cgi/reprint/91/10/1700.pdf.         9 Victoria A. Funk. Phylogenetic patterns and hybridization. In Annals of the Missouri Botanical Garden, Vol. 72(4):681-715, 1985.   Keywords: explicit network, from rooted trees, from species tree, hybridization, parsimony, phylogeny. Note: http://www.jstor.org/stable/2399220.         10 Warren H. Wagner. Reticulistics: the recognition of hybrids and their role in cladistics and classification. In Advances in Cladistics: Proceedings of the Second meeting of the Willi Hennig Society (HENNIG II), Pages 63-79, 1983.   Keywords: explicit network, from rooted trees, from species tree, hybridization, parsimony, phylogeny.

11 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.         12 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.         13 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.         14 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.         15 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.         16 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.         17 Marefatollah Mansouri. Counting General Phylogenetic networks. 2020.   Keywords: counting, explicit network, phylogenetic network, phylogeny. Note: https://arxiv.org/abs/2005.14547.         18 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.         19 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.         20 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.         21 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.         22 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.         23 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.         24 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.         25 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.         26 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.         27 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.         28 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.         29 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.         30 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.         31 Stefan Forcey and Drew Scalzo. Galois connections for phylogenetic networks and their polytopes. 2020.   Keywords: characterization, from distances, galled tree, planar, reconstruction, split network. Note: https://arxiv.org/abs/2004.11944.         32 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.         33 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.         34 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.         35 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.         36 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.         37 Steven Kelk, Fabio Pardi, Celine Scornavacca and Leo van Iersel. Finding the most parsimonious or likely tree in a network with respect to an alignment. In JOMB, Vol. 78:527-547, 2019.   Keywords: APX hard, from network, from sequences, likelihood, NP complete, parsimony. Note: https://arxiv.org/abs/1707.03648.         38 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.         39 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.         40 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.         41 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.         42 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.         43 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.         44 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.         45 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.         46 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         47 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.         48 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.         49 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.         50 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.         51 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.         52 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.         53 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.         54 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.         55 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.         56 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.         57 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.         58 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.         59 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.         60 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.         61 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.         62 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.         63 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.         64 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.         65 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.         66 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.         67 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.         68 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.         69 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.         70 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/.         71 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.         72 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. Note: https://arxiv.org/abs/1707.09579         73 Sarah Bastkowski, Daniel Mapleson, Andreas Spillner, Taoyang Wu, Monika Balvociute and Vincent Moulton. SPECTRE: a Suite of PhylogEnetiC Tools for Reticulate Evolution. In BIO, Vol. 34(6):1057-1058, 2018.   Keywords: abstract network, NeighborNet, phylogenetic network, phylogeny, Program FlatNJ, Program QNet, Program SplitsTree, reconstruction, software, split network. Note: https://doi.org/10.1101/169177.         74 Sebastien Roch and Kun-Chieh Wang. Circular Networks from Distorted Metrics. In RECOMB18, Vol. 10812:167-176 of LNCS, Springer, 2018.   Keywords: abstract network, circular split system, from distances, NeighborNet, phylogenetic network, phylogeny, reconstruction, split network. Note: https://arxiv.org/abs/1707.05722.         75 Paul Bastide, Claudia Solís-Lemus, Ricardo Kriebel, Kenneth William Sparks and Cécile Ané. Phylogenetic Comparative Methods on Phylogenetic Networks with Reticulations. In SB, Vol. 67(5):800-820, 2018.   Keywords: ancestral trait reconstruction, from network, likelihood, Program PhyloNetworks SNaQ, software, statistical model, statistical test. Note: https://doi.org/10.1101/194050.         76 Katharina Huber, Vincent Moulton, Charles Semple and Taoyang Wu. Quarnet inference rules for level-1 networks. 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Efficient Algorithms for Trees and Networks in Evolutionary Genomics. PhD thesis, University of Connecticut, 2018.   Keywords: branch length, explicit network, haplotype network, heuristic, Program PIRN, reconstruction. Note: https://opencommons.uconn.edu/dissertations/1853.         86 Charles Semple and Jack Simpson. When is a phylogenetic network simply an amalgamation of two trees? In BMB, Vol. 80(9):2338-2348, 2018.   Keywords: characterization, phylogenetic network, phylogeny, reticulation-visible network, stack-free network, tree-based network. Note: http://www.math.canterbury.ac.nz/~c.semple/papers/SS18.pdf.         87 Magnus Bordewich, Katharina Huber, Vincent Moulton and Charles Semple. Recovering normal networks from shortest inter-taxa distance information. In JOMB, Vol. 77(3):571-594, 2018.   Keywords: explicit network, from distances, normal network, phylogenetic network, phylogeny, polynomial, reconstruction, uniqueness. 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In SB, Vol. 67(3):439-457, 2018.   Keywords: bayesian, explicit network, from sequences, incomplete lineage sorting, phylogenetic network, phylogeny, Program PhyloNet, reconstruction. Note: https://doi.org/10.1093/sysbio/syx085.         97 Andreas Gunawan. On the tree and cluster containment problems for phylogenetic networks. PhD thesis, National University of Singapore, 2018.   Keywords: cluster containment, explicit network, galled network, genetically stable network, nearly-stable network, phylogenetic network, phylogeny, reticulation-visible network, tree containment. Note: https://scholarbank.nus.edu.sg/handle/10635/144270.         98 Leo van Iersel, Remie Janssen, Mark Jones, Yukihiro Murakami and Norbert Zeh. Polynomial-Time Algorithms for Phylogenetic Inference Problems. In AlCoB18, Vol. 10849:37-49 of LNCS, Springer, 2018.   Keywords: hybridization, minimum number, parental hybridization, phylogenetic network, phylogeny, polynomial, reconstruction, weakly displaying. 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In JOMB, Vol. 74(7):1729-1751, 2017.   Keywords: from clusters, from triplets, galled tree, phylogenetic network, phylogeny, reconstruction, uniqueness. Note: http://dx.doi.org/10.1007/s00285-016-1068-3.         105 Philippe Gambette, Katharina Huber and Guillaume Scholz. Uprooted Phylogenetic Networks. In BMB, Vol. 79(9):2022-2048, 2017.   Keywords: circular split system, explicit network, from splits, galled tree, phylogenetic network, phylogeny, polynomial, reconstruction, split network, uniqueness. Note: http://arxiv.org/abs/1511.08387.         106 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.         107 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.         108 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.         109 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.         110 Gabriel Cardona and Joan Carles Pons. Reconstruction of LGT networks from tri-LGT-nets. In JOMB, Vol. 75(6-7):1669-1692, 2017.   Keywords: explicit network, from subnetworks, from tri-LGT-nets, LGT network, phylogenetic network, phylogeny, reconstruction, uniqueness. Note: https://doi.org/10.1007/s00285-017-1171-0.         111 Bingxin Lu, Louxin Zhang and Hon Wai Leong. A program to compute the soft Robinson-Foulds distance between phylogenetic networks. In APBC17, Vol. 18(Suppl. 2):111 of BMC Genomics, 2017.   Keywords: cluster containment, distance between networks, explicit network, exponential algorithm, from network, phylogenetic network, phylogeny, Program icelu-PhyloNetwork. Note: http://dx.doi.org/10.1186/s12864-017-3500-5.         112 Vincent Moulton, James Oldman and Taoyang Wu. A cubic-time algorithm for computing the trinet distance between level-1 networks. In IPL, Vol. 123:36-41, 2017.   Keywords: distance between networks, explicit network, from network, phylogenetic network, phylogeny, polynomial, Program TriLoNet. Note: https://doi.org/10.1016/j.ipl.2017.03.002.         113 Magnus Bordewich, Simone Linz and Charles Semple. Lost in space? Generalising subtree prune and regraft to spaces of phylogenetic networks. In JTB, Vol. 423:1-12, 2017.   Keywords: distance between networks, explicit network, phylogenetic network, phylogeny, reticulation-visible network, SPR distance, tree-based network, tree-child network. Note: https://simonelinz.files.wordpress.com/2017/04/bls171.pdf.         114 Celine Scornavacca, Joan Carles Pons and Gabriel Cardona. Fast algorithm for the reconciliation of gene trees and LGT networks. In JTB, Vol. 418:129-137, 2017.   Keywords: duplication, explicit network, from network, from rooted trees, lateral gene transfer, LGT network, loss, parsimony, phylogenetic network, phylogeny, polynomial, reconstruction.         115 Jesper Jansson, Ramesh Rajaby and Wing-Kin Sung. An Efficient Algorithm for the Rooted Triplet Distance Between Galled Trees. In AlCoB17, Vol. 10252:115-126 of LNCS, Springer, 2017.   Keywords: distance between networks, from network, phylogenetic network, phylogeny, polynomial, reconstruction, triplet distance. Note: .         116 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.         117 Juan Wang and Maozu Guo. A Metric on the Space of kth-order reduced Phylogenetic Networks. In Scientific Reports, Vol. 7(3189):1-10, 2017.   Keywords: distance between networks, explicit network, from network, kth-order reduced network, phylogenetic network, phylogeny, polynomial. Note: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5466651/.         118 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. 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In AEEICB17, Pages 202-206, IEEE, 2017.   Keywords: from triplets, phylogenetic network, phylogeny, Program TripNet, reconstruction.         122 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.         123 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.         124 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.         125 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.         126 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.         127 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.         128 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.         129 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.         130 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..         131 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.         132 Dingqiao Wen. Bayesian Inference of Phylogenetic Networks from Sequence Data. PhD thesis, Rice University, 2017.   Keywords: bayesian, explicit network, phylogenetic network, phylogeny, reconstruction.         133 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.         134 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. 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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 .         141 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.         142 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.         143 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.         144 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.         145 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.         146 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.         147 Rinku Mathur and Neeru Adlakha. A graph theoretic model for prediction of reticulation events and phylogenetic networks for DNA sequences. In Egyptian Journal of Basic and Applied Sciences, Vol. 3(3):263-271, 2016.   Keywords: from sequences, phylogenetic network, phylogeny, Program T REX. Note: http://dx.doi.org/10.1016/j.ejbas.2016.07.004.         148 Andreas Gunawan, Bingxin Lu and Louxin Zhang. A program for verification of phylogenetic network models. In ECCB16, Vol. 32(17):i503-i510 of BIO, 2016.   Keywords: exponential algorithm, from network, from rooted trees, phylogenetic network, phylogeny, software, tree containment. Note: http://dx.doi.org/10.1093/bioinformatics/btw467.         149 Hussein A. Hejase and Kevin J. Liu. A scalability study of phylogenetic network inference methods using empirical datasets and simulations involving a single reticulation. Vol. 17(422):1-12, 2016.   Keywords: abstract network, evaluation, from sequences, phylogenetic network, phylogeny, Program PhyloNet, Program PhyloNetworks SNaQ, reconstruction, simulation, unicyclic network. Note: http://dx.doi.org/10.1186/s12859-016-1277-1.         150 Ioannis G. Tollis and Konstantinos G. Kakoulis. Algorithms for Visualizing Phylogenetic Networks. In GD16, Vol. 9801:183-195 of LNCS, springer, 2016.   Keywords: explicit network, galled network, galled tree, NP complete, planar, visualization. Note: http://arxiv.org/abs/1609.00755.         151 Philippe Gambette, Leo van Iersel, Steven Kelk, Fabio Pardi and Celine Scornavacca. Do branch lengths help to locate a tree in a phylogenetic network? In BMB, Vol. 78(9):1773-1795, 2016.   Keywords: branch length, explicit network, FPT, from network, from rooted trees, NP complete, phylogenetic network, phylogeny, pseudo-polynomial, time consistent network, tree containment, tree sibling network. Note: http://arxiv.org/abs/1607.06285.         152 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.         153 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. Note: http://www.math.canterbury.ac.nz/~c.semple/papers/S15.pdf.         154 Katharina Huber, Vincent Moulton and Taoyang Wu. Transforming phylogenetic networks: Moving beyond tree space. In JTB, Vol. 404:30-39, 2016.   Keywords: distance between networks, level k phylogenetic network, NNI moves, phylogenetic network, phylogeny. Note: http://arxiv.org/abs/1601.01788.         155 Maria Anaya, Olga Anipchenko-Ulaj, Aisha Ashfaq, Joyce Chiu, Mahedi Kaiser, Max Shoji Ohsawa, Megan Owen, Ella Pavlechko, Katherine St. John, Shivam Suleria, Keith Thompson and Corrine Yap. On Determining if Tree-based Networks Contain Fixed Trees. In BMB, Vol. 78(5):961-969, 2016.   Keywords: explicit network, FPT, NP complete, phylogenetic network, phylogeny, tree-based network. Note: http://arxiv.org/abs/1602.02739.         156 Momoko Hayamizu. On the existence of infinitely many universal tree-based networks. In JTB, Vol. 396:204-206, 2016.   Keywords: explicit network, phylogenetic network, phylogeny, tree-based network. Note: http://arxiv.org/abs/1512.02402.         157 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.         158 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.         159 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.         160 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.         161 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. Note: http://arxiv.org/abs/1606.07350.         162 Magnus Bordewich and Nihan Tokac. An algorithm for reconstructing ultrametric tree-child networks from inter-taxa distances. In DAM, Vol. 213:47-59, 2016.   Keywords: explicit network, from distances, phylogenetic network, phylogeny, reconstruction, tree-child network. Note: http://dx.doi.org/10.1016/j.dam.2016.05.011.         163 Juan Wang, Zhang Zhibin and Yanjuan Li. Constructing phylogenetic networks based on the isomorphism of datasets. In BMRI, Vol. 2016(4236858):1-7, 2016.   Keywords: from clusters, phylogenetic network, phylogeny, reconstruction. Note: http://downloads.hindawi.com/journals/bmri/aip/4236858.pdf.         164 Dan Graur. Reticulate evolution and phylogenetic networks. In Molecular and Genome Evolution, Chapter 6, Sinauer, 2016.   Keywords: phylogenetic network, phylogeny, survey. Note: http://www.sinauer.com/media/wysiwyg/samples/Graur_MGE1e_Ch06.pdf.         165 Mike Steel. Introduction to phylogenetic networks. In Phylogeny: Discrete and Random Processes in Evolution, Vol. 89 of CBMS-NSF Regional Conference Series in Applied Mathematics, Chapter 10, SIAM, 2016.   Keywords: abstract network, explicit network, phylogenetic network, phylogeny, survey. Note: http://bookstore.siam.org/cb89/.         166 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.         167 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/.         168 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.         169 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.         170 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.         171 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.         172 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.         173 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.         174 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.         175 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.         176 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.         177 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.         178 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.         179 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.         180 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.         181 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.         182 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.         183 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.         184 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.         185 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.         186 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.         187 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.         188 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.         189 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.         190 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.         191 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.         192 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.         193 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.         194 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.         195 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.         196 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.         197 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.         198 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.         199 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.         200 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.         201 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.         202 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.         203 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.         204 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.         205 Claudia Solís-Lemus. Statistical methods to infer population structure with coalescence and gene flow. PhD thesis, University of Wisconsin-Madison, 2015.   Keywords: explicit network, from quartets, from unrooted trees, likelihood, phylogenetic network, phylogeny, Program PhyloNetworks SNaQ, semidirected network. Note: https://www.stat.wisc.edu/~claudia/thesis.pdf.         206 Leo van Iersel, Steven Kelk, Nela Lekic and Leen Stougie. Approximation algorithms for nonbinary agreement forests. In SIDMA, Vol. 28(1):49-66, 2014.   Keywords: agreement forest, approximation, from rooted trees, hybridization, minimum number, phylogenetic network, phylogeny, reconstruction. Note: http://arxiv.org/abs/1210.3211.         Toggle abstract "Given two rooted phylogenetic trees on the same set of taxa X, the Maximum Agreement Forest (maf) problem asks to find a forest that is, in a certain sense, common to both trees and has a minimum number of components. The Maximum Acyclic Agreement Forest (maaf) problem has the additional restriction that the components of the forest cannot have conflicting ancestral relations in the input trees. There has been considerable interest in the special cases of these problems in which the input trees are required to be binary. However, in practice, phylogenetic trees are rarely binary, due to uncertainty about the precise order of speciation events. Here, we show that the general, nonbinary version of maf has a polynomial-time 4-approximation and a fixedparameter tractable (exact) algorithm that runs in O(4opoly(n)) time, where n = |X| and k is the number of components of the agreement forest minus one. Moreover, we show that a c-approximation algorithm for nonbinary maf and a d-approximation algorithm for the classical problem Directed Feedback Vertex Set (dfvs) can be combined to yield a d(c+3)-approximation for nonbinary maaf. The algorithms for maf have been implemented and made publicly available. © 2014 Society for Industrial and Applied Mathematics." 207 Gabriel Cardona, Mercè Llabrés, Francesc Rosselló and Gabriel Valiente. The comparison of tree-sibling time consistent phylogenetic networks is graph-isomorphism complete. In The Scientific World Journal, Vol. 2014(254279):1-6, 2014.   Keywords: abstract network, distance between networks, from network, isomorphism, phylogenetic network, tree sibling network. Note: http://arxiv.org/abs/0902.4640.         Toggle abstract "Several polynomial time computable metrics on the class of semibinary tree-sibling time consistent phylogenetic networks are available in the literature; in particular, the problem of deciding if two networks of this kind are isomorphic is in P. In this paper, we show that if we remove the semibinarity condition, then the problem becomes much harder. More precisely, we prove that the isomorphism problem for generic tree-sibling time consistent phylogenetic networks is polynomially equivalent to the graph isomorphism problem. Since the latter is believed not to belong to P, the chances are that it is impossible to define a metric on the class of all tree-sibling time consistent phylogenetic networks that can be computed in polynomial time. © 2014 Gabriel Cardona et al." 208 Steven Kelk and Celine Scornavacca. Constructing minimal phylogenetic networks from softwired clusters is fixed parameter tractable. In ALG, Vol. 68(4):886-915, 2014.   Keywords: explicit network, FPT, from clusters, level k phylogenetic network, phylogenetic network, phylogeny, reconstruction. Note: http://arxiv.org/abs/1108.3653.         Toggle abstract "Here we show that, given a set of clusters C on a set of taxa X, where |X|=n, it is possible to determine in time f(k)×poly(n) whether there exists a level-≤k network (i.e. a network where each biconnected component has reticulation number at most k) that represents all the clusters in C in the softwired sense, and if so to construct such a network. This extends a result from Kelk et al. (in IEEE/ACM Trans. Comput. Biol. Bioinform. 9:517-534, 2012) which showed that the problem is polynomial-time solvable for fixed k. By defining "k-reticulation generators" analogous to "level-k generators", we then extend this fixed parameter tractability result to the problem where k refers not to the level but to the reticulation number of the whole network. © 2012 Springer Science+Business Media New York." 209 Hadi Poormohammadi, Changiz Eslahchi and Ruzbeh Tusserkani. TripNet: A Method for Constructing Rooted Phylogenetic Networks from Rooted Triplets. In PLoS ONE, Vol. 9(9):e106531, 2014.   Keywords: explicit network, from triplets, heuristic, level k phylogenetic network, phylogenetic network, phylogeny, Program TripNet, reconstruction, software. Note: http://arxiv.org/abs/1201.3722.         Toggle abstract "The problem of constructing an optimal rooted phylogenetic network from an arbitrary set of rooted triplets is an NP-hard problem. In this paper, we present a heuristic algorithm called TripNet, which tries to construct a rooted phylogenetic network with the minimum number of reticulation nodes from an arbitrary set of rooted triplets. Despite of current methods that work for dense set of rooted triplets, a key innovation is the applicability of TripNet to non-dense set of rooted triplets. We prove some theorems to clarify the performance of the algorithm. To demonstrate the efficiency of TripNet, we compared TripNet with SIMPLISTIC. It is the only available software which has the ability to return some rooted phylogenetic network consistent with a given dense set of rooted triplets. But the results show that for complex networks with high levels, the SIMPLISTIC running time increased abruptly. However in all cases TripNet outputs an appropriate rooted phylogenetic network in an acceptable time. Also we tetsed TripNet on the Yeast data. The results show that Both TripNet and optimal networks have the same clustering and TripNet produced a level-3 network which contains only one more reticulation node than the optimal network." 210 Sven Herrmann and Vincent Moulton. Computing the blocks of a quasi-median graph. In DAM, Vol. 179:129-138, 2014.   Keywords: abstract network, from sequences, phylogenetic network, phylogeny, polynomial, Program QuasiDec, quasi-median network, reconstruction. Note: http://arxiv.org/abs/1206.6135.         211 Leo van Iersel and Vincent Moulton. Trinets encode tree-child and level-2 phylogenetic networks. In JOMB, Vol. 68(7):1707-1729, 2014.   Keywords: explicit network, from subnetworks, from trinets, level k phylogenetic network, phylogenetic network, phylogeny, reconstruction. Note: http://arxiv.org/abs/1210.0362.         Toggle abstract "Phylogenetic networks generalize evolutionary trees, and are commonly used to represent evolutionary histories of species that undergo reticulate evolutionary processes such as hybridization, recombination and lateral gene transfer. Recently, there has been great interest in trying to develop methods to construct rooted phylogenetic networks from triplets, that is rooted trees on three species. However, although triplets determine or encode rooted phylogenetic trees, they do not in general encode rooted phylogenetic networks, which is a potential issue for any such method. Motivated by this fact, Huber and Moulton recently introduced trinets as a natural extension of rooted triplets to networks. In particular, they showed that level-1 phylogenetic networks are encoded by their trinets, and also conjectured that all "recoverable" rooted phylogenetic networks are encoded by their trinets. Here we prove that recoverable binary level-2 networks and binary tree-child networks are also encoded by their trinets. To do this we prove two decomposition theorems based on trinets which hold for all recoverable binary rooted phylogenetic networks. Our results provide some additional evidence in support of the conjecture that trinets encode all recoverable rooted phylogenetic networks, and could also lead to new approaches to construct phylogenetic networks from trinets. © 2013 Springer-Verlag Berlin Heidelberg." 212 Anthony Labarre and Sicco Verwer. Merging partially labelled trees: hardness and a declarative programming solution. In TCBB, Vol. 11(2):389-397, 2014.   Keywords: abstract network, from unrooted trees, heuristic, NP complete, phylogenetic network, phylogeny, reconstruction. Note: https://hal-upec-upem.archives-ouvertes.fr/hal-00855669.         Toggle abstract "Intraspecific studies often make use of haplotype networks instead of gene genealogies to represent the evolution of a set of genes. Cassens et al. proposed one such network reconstruction method, based on the global maximum parsimony principle, which was later recast by the first author of the present work as the problem of finding a minimum common supergraph of a set of t partially labelled trees. Although algorithms have been proposed for solving that problem on two graphs, the complexity of the general problem on trees remains unknown. In this paper, we show that the corresponding decision problem is NP-complete for t=3. We then propose a declarative programming approach to solving the problem to optimality in practice, as well as a heuristic approach, both based on the idpsystem, and assess the performance of both methods on randomly generated data. © 2004-2012 IEEE." 213 Judith Keijsper and Rudi Pendavingh. Reconstructing a phylogenetic level-1 network from quartets. In BMB, Vol. 76(10):2517-2541, 2014.   Keywords: explicit network, from quartets, galled tree, phylogenetic network, phylogeny, polynomial, reconstruction. Note: http://arxiv.org/abs/1308.5206.         214 Leo van Iersel and Steven Kelk. Kernelizations for the hybridization number problem on multiple nonbinary trees. In WG14, Vol. 8747:299-311 of LNCS, springer, 2014.   Keywords: explicit network, from rooted trees, kernelization, minimum number, phylogenetic network, phylogeny, Program Treeduce, reconstruction. Note: http://arxiv.org/abs/1311.4045.         215 Jesper Jansson and Andrzej Lingas. Computing the rooted triplet distance between galled trees by counting triangles. In Journal of Discrete Algorithms, Vol. 25:66-78, 2014.   Keywords: distance between networks, explicit network, from network, galled network, phylogenetic network, phylogeny, polynomial, triplet distance.         Toggle abstract "We consider a generalization of the rooted triplet distance between two phylogenetic trees to two phylogenetic networks. We show that if each of the two given phylogenetic networks is a so-called galled tree with n leaves then the rooted triplet distance can be computed in o(n2.687) time. Our upper bound is obtained by reducing the problem of computing the rooted triplet distance between two galled trees to that of counting monochromatic and almost-monochromatic triangles in an undirected, edge-colored graph. To count different types of colored triangles in a graph efficiently, we extend an existing technique based on matrix multiplication and obtain several new algorithmic results that may be of independent interest: (i) the number of triangles in a connected, undirected, uncolored graph with m edges can be computed in o(m1.408) time; (ii) if G is a connected, undirected, edge-colored graph with n vertices and C is a subset of the set of edge colors then the number of monochromatic triangles of G with colors in C can be computed in o(n2.687) time; and (iii) if G is a connected, undirected, edge-colored graph with n vertices and R is a binary relation on the colors that is computable in O(1) time then the number of R-chromatic triangles in G can be computed in o(n2.687) time. © 2013 Elsevier B.V. All rights reserved." 216 Ward C Wheeler. Phyletic groups on networks. In Cladistics, Vol. 30(4):447-451, 2014.   Keywords: explicit network, from network, phylogenetic network, phylogeny. Note: http://dx.doi.org/10.1111/cla.12062.         Toggle abstract "Three additional phyletic group types, "periphyletic," "epiphyletic", and "anaphyletic" (in addition to Hennigian mono-, para-, and polyphyletic) are defined in terms of trees and phylogenetic networks (trees with directed reticulate edges) via a generalization of the algorithmic definitions of Farris. These designations concern groups defined as monophyletic on trees, but with additional gains or losses of members from network edges. These distinctions should be useful in discussion of systems with non-vertical inheritance such as recombination between viruses, horizontal exchange between bacteria, hybridization in plants and animals, as well as human linguistic evolution. Examples are illustrated with Indo-European language groups. © The Willi Hennig Society 2013." 217 Sarah Bastkowski, Andreas Spillner and Vincent Moulton. Fishing for minimum evolution trees with Neighbor-Nets. In IPL, Vol. 114(1-2):3-18, 2014.   Keywords: circular split system, from distances, NeighborNet, phylogeny, polynomial.         Toggle abstract "In evolutionary biology, biologists commonly use a phylogenetic tree to represent the evolutionary history of some set of species. A common approach taken to construct such a tree is to search through the space of all possible phylogenetic trees on the set so as to find one that optimizes some score function, such as the minimum evolution criterion. However, this is hampered by the fact that the space of phylogenetic trees is extremely large in general. Interestingly, an alternative approach, which has received somewhat less attention in the literature, is to instead search for trees within some set of bipartitions or splits of the set of species in question. Here we consider the problem of searching through a set of splits that is circular. Such sets can, for example, be generated by the NeighborNet algorithm for constructing phylogenetic networks. More specifically, we present an O(n4) time algorithm for finding an optimal minimum evolution tree in a circular set of splits on a set of species of size n. In addition, using simulations, we compare the performance of this algorithm when applied to NeighborNet output with that of FastME, a leading method for searching for minimum evolution trees in tree space. We find that, even though a circular set of splits represents just a tiny fraction of the total number of possible splits of a set, the trees obtained from circular sets compare quite favorably with those obtained with FastME, suggesting that the approach could warrant further investigation. © 2013 Elsevier B.V." 218 Lavanya Kannan and Ward C Wheeler. Exactly Computing the Parsimony Scores on Phylogenetic Networks Using Dynamic Programming. In JCB, Vol. 21(4):303-319, 2014.   Keywords: explicit network, exponential algorithm, from network, from sequences, parsimony, phylogenetic network, phylogeny, reconstruction.         Toggle abstract "Scoring a given phylogenetic network is the first step that is required in searching for the best evolutionary framework for a given dataset. Using the principle of maximum parsimony, we can score phylogenetic networks based on the minimum number of state changes across a subset of edges of the network for each character that are required for a given set of characters to realize the input states at the leaves of the networks. Two such subsets of edges of networks are interesting in light of studying evolutionary histories of datasets: (i) the set of all edges of the network, and (ii) the set of all edges of a spanning tree that minimizes the score. The problems of finding the parsimony scores under these two criteria define slightly different mathematical problems that are both NP-hard. In this article, we show that both problems, with scores generalized to adding substitution costs between states on the endpoints of the edges, can be solved exactly using dynamic programming. We show that our algorithms require O(mpk) storage at each vertex (per character), where k is the number of states the character can take, p is the number of reticulate vertices in the network, m = k for the problem with edge set (i), and m = 2 for the problem with edge set (ii). This establishes an O(nmpk2) algorithm for both the problems (n is the number of leaves in the network), which are extensions of Sankoff's algorithm for finding the parsimony scores for phylogenetic trees. We will discuss improvements in the complexities and show that for phylogenetic networks whose underlying undirected graphs have disjoint cycles, the storage at each vertex can be reduced to O(mk), thus making the algorithm polynomial for this class of networks. We will present some properties of the two approaches and guidance on choosing between the criteria, as well as traverse through the network space using either of the definitions. We show that our methodology provides an effective means to study a wide variety of datasets. © Copyright 2014, Mary Ann Liebert, Inc. 2014." 219 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." 220 Ran Libeskind-Hadas, Yi-Chieh Wu, Mukul S. Bansal and Manolis Kellis. Pareto-optimal phylogenetic tree reconciliation. In ISMB14, Vol. 30:i87-i95 of BIO, 2014.   Keywords: duplication, lateral gene transfer, loss, phylogenetic network, phylogeny, polynomial, Program Xscape, reconstruction. Note: http://dx.doi.org/10.1093/bioinformatics/btu289.         Toggle abstract "Motivation: Phylogenetic tree reconciliation is a widely used method for reconstructing the evolutionary histories of gene families and species, hosts and parasites and other dependent pairs of entities. Reconciliation is typically performed using maximum parsimony, in which each evolutionary event type is assigned a cost and the objective is to find a reconciliation of minimum total cost. It is generally understood that reconciliations are sensitive to event costs, but little is understood about the relationship between event costs and solutions. Moreover, choosing appropriate event costs is a notoriously difficult problem. Results: We address this problem by giving an efficient algorithm for computing Pareto-optimal sets of reconciliations, thus providing the first systematic method for understanding the relationship between event costs and reconciliations. This, in turn, results in new techniques for computing event support values and, for cophylogenetic analyses, performing robust statistical tests. We provide new software tools and demonstrate their use on a number of datasets from evolutionary genomic and cophylogenetic studies. © 2014 The Author. Published by Oxford University Press. All rights reserved." 221 Kevin J. Liu, Jingxuan Dai, Kathy Truong, Ying Song, Michael H. Kohn and Luay Nakhleh. An HMM-Based Comparative Genomic Framework for Detecting Introgression in Eukaryotes. In PLoS ONE, Vol. 10(6):e1003649, 2014.   Keywords: explicit network, from network, phylogenetic network, phylogeny, Program PhyloNet-HMM. Note: http://arxiv.org/abs/1310.7989.         Toggle abstract "One outcome of interspecific hybridization and subsequent effects of evolutionary forces is introgression, which is the integration of genetic material from one species into the genome of an individual in another species. The evolution of several groups of eukaryotic species has involved hybridization, and cases of adaptation through introgression have been already established. In this work, we report on PhyloNet-HMM-a new comparative genomic framework for detecting introgression in genomes. PhyloNet-HMM combines phylogenetic networks with hidden Markov models (HMMs) to simultaneously capture the (potentially reticulate) evolutionary history of the genomes and dependencies within genomes. A novel aspect of our work is that it also accounts for incomplete lineage sorting and dependence across loci. Application of our model to variation data from chromosome 7 in the mouse (Mus musculus domesticus) genome detected a recently reported adaptive introgression event involving the rodent poison resistance gene Vkorc1, in addition to other newly detected introgressed genomic regions. Based on our analysis, it is estimated that about 9% of all sites within chromosome 7 are of introgressive origin (these cover about 13 Mbp of chromosome 7, and over 300 genes). Further, our model detected no introgression in a negative control data set. We also found that our model accurately detected introgression and other evolutionary processes from synthetic data sets simulated under the coalescent model with recombination, isolation, and migration. Our work provides a powerful framework for systematic analysis of introgression while simultaneously accounting for dependence across sites, point mutations, recombination, and ancestral polymorphism. © 2014 Liu et al." 222 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.         223 David A. Morrison. Rooted Phylogenetic Networks for Exploratory Data Analysis. In Advances in Research, Vol. 2(3):145-152, 2014.   Keywords: abstract network, explicit network, phylogenetic network, reconstruction.         224 David A. Morrison. Next generation sequencing and phylogenetic networks. In EMBnet.journal, Vol. 20(e760):1-4, 2014.   Keywords: abstract network, from NGS data, phylogenetic network, phylogeny, Program SplitsTree, reconstruction.         225 Dan Gusfield. ReCombinatorics: The Algorithmics of Ancestral Recombination Graphs and Explicit Phylogenetic Networks. MIT Press, 2014.   Keywords: ARG, explicit network, phylogenetic network, phylogeny, survey. Note: http://mitpress.mit.edu/books/recombinatorics.         226 Josh Voorkamp né Collins. Untangling Evolution. PhD thesis, University of Otago, New Zealand, 2014.   Keywords: agreement forest, explicit network, from rooted trees, generation, phylogenetic network, phylogeny, reconstruction. Note: http://otago.ourarchive.ac.nz/handle/10523/4802.         227 Vladimir Makarenkov, Alix Boc and Pierre Legendre. A New Algorithm for Inferring Hybridization Events Based on the Detection of Horizontal Gene Transfers. In Fuad Aleskerov, Boris Goldengorin and Panos M. Pardalos editors, Clusters, Orders, and Trees: Methods and Applications, Vol. 92 of Springer Optimization and Its Applications, Springer, 2014.   Keywords: explicit network, phylogenetic network, phylogeny, reconstruction.         228 Leo van Iersel, Steven Kelk, Nela Lekic and Celine Scornavacca. A practical approximation algorithm for solving massive instances of hybridization number for binary and nonbinary trees. In BMCB, Vol. 15(127):1-12, 2014.   Keywords: agreement forest, approximation, explicit network, from rooted trees, phylogenetic network, phylogeny, Program CycleKiller, Program TerminusEst, reconstruction. Note: http://dx.doi.org/10.1186/1471-2105-15-127.         229 Yi-Chieh Wu. Computational evolutionary genomics : phylogenomic models spanning domains, genes, individuals, and species. PhD thesis, Massachusetts Institute of Technology, U.S.A., 2014.   Keywords: duplication, from sequences, from species tree, lateral gene transfer, loss, phylogeny, Program TreeFix-DTL, reconstruction. Note: http://hdl.handle.net/1721.1/87937.         230 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." 231 Johann-Mattis List, Shijulal Nelson-Sathi, Hans Geisler and William Martin. Networks of lexical borrowing and lateral gene transfer in language and genome evolution. In BioEssays, Vol. 36(2):141-150, 2014.   Keywords: explicit network, minimal lateral network, phylogenetic network, Program lingpy. Note: http://dx.doi.org/10.1002/bies.201300096.         Toggle abstract "Like biological species, languages change over time. As noted by Darwin, there are many parallels between language evolution and biological evolution. Insights into these parallels have also undergone change in the past 150 years. Just like genes, words change over time, and language evolution can be likened to genome evolution accordingly, but what kind of evolution? There are fundamental differences between eukaryotic and prokaryotic evolution. In the former, natural variation entails the gradual accumulation of minor mutations in alleles. In the latter, lateral gene transfer is an integral mechanism of natural variation. The study of language evolution using biological methods has attracted much interest of late, most approaches focusing on language tree construction. These approaches may underestimate the important role that borrowing plays in language evolution. Network approaches that were originally designed to study lateral gene transfer may provide more realistic insights into the complexities of language evolution. Editor's suggested further reading in BioEssays Linguistic evidence supports date for Homeric epics. © 2014 The Authors. BioEssays Published by WILEY Periodicals, Inc." 232 Benjamin Albrecht. Computing Hybridization Networks for Multiple Rooted Binary Phylogenetic Trees by Maximum Acyclic Agreement Forests. 2014.   Keywords: agreement forest, from rooted trees, minimum number, phylogenetic network, phylogeny, polynomial, Program Hybroscale, reconstruction. Note: http://arxiv.org/abs/1408.3044.         233 Puspal Bhabak and Asish Mukhopadhyay. A 3-factor approximation algorithm for a Minimum Acyclic Agreement Forest on k rooted, binary phylogenetic trees. 2014.   Keywords: agreement forest, approximation, explicit network, from rooted trees, phylogenetic network, phylogeny, reconstruction. Note: http://arxiv.org/abs/1407.7125.