Who is Who in Phylogenetic Networks

Publications related to 'evaluation' : Publications tagged with the evaluation keyword compare different phylogenetic network reconstruction methods. Note that articles tagged with generation or distance between networks may also be interesting regarding evaluation of network reconstruction methods.   Order by:   Type | Year

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Associated keywords

abstract-network branch-length circular-split-system cluster-containment coalescent consensus distance-between-networks evaluation explicit-network exponential-algorithm FPT from-clusters from-distances from-network from-rooted-trees from-sequences from-species-tree from-triplets from-unrooted-trees galled-tree generation genetically-stable-network haplotype-network hybridization incomplete-lineage-sorting lateral-gene-transfer level-k-phylogenetic-network median-network MedianJoining minimum-spanning-network mu-distance nearly-stable-network NeighborNet NP-complete parsimony phylogenetic-network phylogeny polynomial Program-Arlequin Program-BIMLR Program-Bio-PhyloNetwork Program-CombineTrees Program-Dendroscope Program-EEEP Program-HorizStory Program-LatTrans Program-Level2 Program-LNetwork Program-Marlon Program-NetGen Program-Network Program-PhyloNet Program-PhyloNetworks-SNaQ Program-Pyramids Program-Recodon Program-SHRUB Program-Simplistic Program-SplitsTree Program-SPNet Program-T-REX Program-TCS pyramid recombination recombination-detection reconstruction regular-network reticulogram simulation software split split-decomposition split-network SPR-distance statistical-model survey time-consistent-network tree-containment tree-sibling-network tree-based-network tree-child-network tripartition-distance unicyclic-network visualization weak-hierarchy weakly-displaying

Article (Journal)

1 François-Joseph Lapointe. How to account for reticulation events in phylogenetic analysis: A review of distance-based methods. In Journal of Classification, Vol. 17:175-184, 2000. Keywords: abstract network, evaluation, from distances, phylogenetic network, Program Pyramids, Program SplitsTree, Program T REX, pyramid, reconstruction, reticulogram, split network, survey, weak hierarchy. Note: http://dx.doi.org/10.1007/s003570000016.         2 Bernard M. E. Moret, Luay Nakhleh, Tandy Warnow, C. Randal Linder, Anna Tholse, Anneke Padolina, Jerry Sun and Ruth Timme. Phylogenetic Networks: Modeling, Reconstructibility, and Accuracy. In TCBB, Vol. 1(1):13-23, 2004. Keywords: distance between networks, evaluation, phylogenetic network, phylogeny, time consistent network, tripartition distance. Note: http://www.cs.rice.edu/~nakhleh/Papers/tcbb04.pdf.         3 Robert G. Beiko and Nicholas Hamilton. Phylogenetic identification of lateral genetic transfer events. In BMCEB, Vol. 6(15), 2006. Keywords: evaluation, from rooted trees, from unrooted trees, lateral gene transfer, Program EEEP, Program HorizStory, Program LatTrans, reconstruction, software, SPR distance. Note: http://dx.doi.org/10.1186/1471-2148-6-15.         Toggle abstract "Background: Lateral genetic transfer can lead to disagreements among phylogenetic trees comprising sequences from the same set of taxa. Where topological discordance is thought to have arisen through genetic transfer events, tree comparisons can be used to identify the lineages that may have shared genetic information. An 'edit path' of one or more transfer events can be represented with a series of subtree prune and regraft (SPR) operations, but finding the optimal such set of operations is NP-hard for comparisons between rooted trees, and may be so for unrooted trees as well. Results: Efficient Evaluation of Edit Paths (EEEP) is a new tree comparison algorithm that uses evolutionarily reasonable constraints to identify and eliminate many unproductive search avenues, reducing the time required to solve many edit path problems. The performance of EEEP compares favourably to that of other algorithms when applied to strictly bifurcating trees with specified numbers of SPR operations. We also used EEEP to recover edit paths from over 19 000 unrooted, incompletely resolved protein trees containing up to 144 taxa as part of a large phylogenomic study. While inferred protein trees were far more similar to a reference supertree than random trees were to each other, the phylogenetic distance spanned by random versus inferred transfer events was similar, suggesting that real transfer events occur most frequently between closely related organisms, but can span large phylogenetic distances as well. While most of the protein trees examined here were very similar to the reference supertree, requiring zero or one edit operations for reconciliation, some trees implied up to 40 transfer events within a single orthologous set of proteins. Conclusion: Since sequence trees typically have no implied root and may contain unresolved or multifurcating nodes, the strategy implemented in EEEP is the most appropriate for phylogenomic analyses. The high degree of consistency among inferred protein trees shows that vertical inheritance is the dominant pattern of evolution, at least for the set of organisms considered here. However, the edit paths inferred using EEEP suggest an important role for genetic transfer in the evolution of microbial genomes as well. © 2006Beiko and Hamilton; licensee BioMed Central Ltd." 4 Maria S. Poptsova and J. Peter Gogarten. The power of phylogenetic approaches to detect horizontally transferred genes. In BMCEB, Vol. 7(45), 2007. Keywords: evaluation, from rooted trees, lateral gene transfer, Program EEEP. Note: http://dx.doi.org/10.1186/1471-2148-7-45.         Toggle abstract "Background. Horizontal gene transfer plays an important role in evolution because it sometimes allows recipient lineages to adapt to new ecological niches. High genes transfer frequencies were inferred for prokaryotic and early eukaryotic evolution. Does horizontal gene transfer also impact phylogenetic reconstruction of the evolutionary history of genomes and organisms? The answer to this question depends at least in part on the actual gene transfer frequencies and on the ability to weed out transferred genes from further analyses. Are the detected transfers mainly false positives, or are they the tip of an iceberg of many transfer events most of which go undetected by current methods? Results. Phylogenetic detection methods appear to be the method of choice to infer gene transfers, especially for ancient transfers and those followed by orthologous replacement. Here we explore how well some of these methods perform using in silico transfers between the terminal branches of a gamma proteobacterial, genome based phylogeny. For the experiments performed here on average the AU test at a 5% significance level detects 90.3% of the transfers and 91% of the exchanges as significant. Using the Robinson-Foulds distance only 57.7% of the exchanges and 60% of the donations were identified as significant. Analyses using bipartition spectra appeared most successful in our test case. The power of detection was on average 97% using a 70% cut-off and 94.2% with 90% cut-off for identifying conflicting bipartitions, while the rate of false positives was below 4.2% and 2.1% for the two cut-offs, respectively. For all methods the detection rates improved when more intervening branches separated donor and recipient. Conclusion. Rates of detected transfers should not be mistaken for the actual transfer rates; most analyses of gene transfers remain anecdotal. The method and significance level to identify potential gene transfer events represent a trade-off between the frequency of erroneous identification (false positives) and the power to detect actual transfer events. © 2007 Poptsova and Gogarten; licensee BioMed Central Ltd." 5 Mohd Abdul Hai Zahid, Ankush Mittal and Ramesh C. Joshi. Use of Phylogenetic network and its reconstruction Algorithms. In Bioinformatics India, Vol. 2:47-58, 2004. Keywords: evaluation, from distances, NeighborNet, Program SplitsTree, Program T REX, split decomposition. Note: http://www.isical.ac.in/~zahid_t/publications/papers/1.pdf.         6 Insa Cassens, Patrick Mardulyn and Michel C. Milinkovitch. Evaluating Intraspecific Network Construction Methods Using Simulated Sequence Data: Do Existing Algorithms Outperform the Global Maximum Parsimony Approach? In Systematic Biology, Vol. 54(3):363-372, 2005. Keywords: abstract network, evaluation, from unrooted trees, haplotype network, parsimony, phylogenetic network, phylogeny, Program Arlequin, Program CombineTrees, Program Network, Program TCS, reconstruction, software. Note: http://www.lanevol.org/LANE/publications_files/Cassens_etal_SystBio_2005.pdf.         7 Dan Levy and Lior Pachter. The Neighbor-Net Algorithm. In Advances in Applied Mathematics, Vol. 47(2):240-258, 2011. Keywords: abstract network, circular split system, evaluation, from distances, NeighborNet, phylogenetic network, phylogeny, split network. Note: http://arxiv.org/abs/math/0702515.         Toggle abstract "The neighbor-joining algorithm is a popular phylogenetics method for constructing trees from dissimilarity maps. The neighbor-net algorithm is an extension of the neighbor-joining algorithm and is used for constructing split networks. We begin by describing the output of neighbor-net in terms of the tessellation of M̄0n(R) by associahedra. This highlights the fact that neighbor-net outputs a tree in addition to a circular ordering and we explain when the neighbor-net tree is the neighbor-joining tree. A key observation is that the tree constructed in existing implementations of neighbor-net is not a neighbor-joining tree. Next, we show that neighbor-net is a greedy algorithm for finding circular split systems of minimal balanced length. This leads to an interpretation of neighbor-net as a greedy algorithm for the traveling salesman problem. The algorithm is optimal for Kalmanson matrices, from which it follows that neighbor-net is consistent and has optimal radius 12. We also provide a statistical interpretation for the balanced length for a circular split system as the length based on weighted least squares estimates of the splits. We conclude with applications of these results and demonstrate the implications of our theorems for a recently published comparison of Papuan and Austronesian languages. © 2010 Elsevier Inc. All rights reserved." 8 Steven M. Woolley, David Posada and Keith A. Crandall. A Comparison of Phylogenetic Network Methods Using Computer Simulation. In PLoS ONE, Vol. 3(4):e1913, 2008. Keywords: abstract network, distance between networks, evaluation, median network, MedianJoining, minimum spanning network, NeighborNet, parsimony, phylogenetic network, phylogeny, Program Arlequin, Program CombineTrees, Program Network, Program SHRUB, Program SplitsTree, Program TCS, split decomposition. Note: http://dx.doi.org/10.1371/journal.pone.0001913.         Toggle abstract "Background: We present a series of simulation studies that explore the relative performance of several phylogenetic network approaches (statistical parsimony, split decomposition, union of maximum parsimony trees, neighbor-net, simulated history recombination upper bound, median-joining, reduced median joining and minimum spanning network) compared to standard tree approaches (neighbor-joining and maximum parsimony) in the presence and absence of recombination. Principal Findings: In the absence of recombination, all methods recovered the correct topology and branch lengths nearly all of the time when the subtitution rate was low, except for minimum spanning networks, which did considerably worse. At a higher substitution rate, maximum parsimony and union of maximum parsimony trees were the most accurate. With recombination, the ability to infer the correct topology was halved for all methods and no method could accurately estimate branch lengths. Conclusions: Our results highlight the need for more accurate phylogenetic network methods and the importance of detecting and accounting for recombination in phylogenetic studies. Furthermore, we provide useful information for choosing a network algorithm and a framework in which to evaluate improvements to existing methods and novel algorithms developed in the future. © 2008 Woolley et al." 9 Shlomo Moran, Sagi Snir and Wing-Kin Sung. Partial Convex Recolorings of Trees and Galled Networks: Tight Upper and Lower bounds. In ACM Transactions on Algorithms, Vol. 7(4), 2011. Keywords: evaluation, galled tree, phylogenetic network. Note: http://www.cs.technion.ac.il/~moran/r/PS/gnets-TOA-7Feb2007.pdf.         Toggle abstract "A coloring of a graph is convex if the vertices that pertain to any color induce a connected subgraph; a partial coloring (which assigns colors to a subset of the vertices) is convex if it can be completed to a convex (total) coloring. Convex coloring has applications in fields such as phylogenetics, communication or transportation networks, etc. When a coloring of a graph is not convex, a natural question is how far it is from a convex one. This problem is denoted as convex recoloring (CR).While the initial works on CR defined and studied the problem on trees, recent efforts aim at either generalizing the underlying graphs or specializing the input colorings. In this work, we extend the underlying graph and the input coloring to partially colored galled networks. We show that although determining whether a coloring is convex on an arbitrary network is hard, it can be found efficiently on galled networks. We present a fixed parameter tractable algorithm that finds the recoloring distance of such a network whose running time is quadratic in the network size and exponential in that distance. This complexity is achieved by amortized analysis that uses a novel technique for contracting colored graphs that seems to be of independent interest. © 2011 ACM." 10 Iyad A. Kanj, Luay Nakhleh, Cuong Than and Ge Xia. Seeing the Trees and Their Branches in the Network is Hard. In TCS, Vol. 401:153-164, 2008. Keywords: evaluation, from network, from rooted trees, NP complete, phylogenetic network, phylogeny, tree containment. Note: http://www.cs.rice.edu/~nakhleh/Papers/tcs08.pdf.         11 Miguel Arenas, Gabriel Valiente and David Posada. Characterization of reticulate networks based on the coalescent with recombination. In MBE, Vol. 25(12):2517-2520, 2008. Keywords: coalescent, evaluation, explicit network, galled tree, phylogenetic network, phylogeny, Program Recodon, regular network, simulation, tree sibling network, tree-child network. Note: http://dx.doi.org/10.1093/molbev/msn219.         Toggle abstract "Phylogenetic networks aim to represent the evolutionary history of taxa. Within these, reticulate networks are explicitly able to accommodate evolutionary events like recombination, hybridization, or lateral gene transfer. Although several metrics exist to compare phylogenetic networks, they make several assumptions regarding the nature of the networks that are not likely to be fulfilled by the evolutionary process. In order to characterize the potential disagreement between the algorithms and the biology, we have used the coalescent with recombination to build the type of networks produced by reticulate evolution and classified them as regular, tree sibling, tree child, or galled trees. We show that, as expected, the complexity of these reticulate networks is a function of the population recombination rate. At small recombination rates, most of the networks produced are already more complex than regular or tree sibling networks, whereas with moderate and large recombination rates, no network fit into any of the standard classes. We conclude that new metrics still need to be devised in order to properly compare two phylogenetic networks that have arisen from reticulating evolutionary process. © 2008 The Authors." 12 Gabriel Cardona, Francesc Rosselló and Gabriel Valiente. Extended Newick: It is Time for a Standard Representation. In BMCB, Vol. 9:532, 2008. Keywords: evaluation, explicit network, phylogenetic network, Program Bio PhyloNetwork, Program Dendroscope, Program NetGen, Program PhyloNet, Program SplitsTree, Program TCS, visualization. Note: http://bioinfo.uib.es/media/uploaded/bmc-2008-enewick-sub.pdf.         13 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.         14 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.         15 Olga K. Kamneva and Noah A. Rosenberg. Simulation-Based Evaluation of Hybridization Network Reconstruction Methods in the Presence of Incomplete Lineage Sorting. In Evolutionary Bioinformatics, Vol. 13(1176934317691935):1-16, 2017. Keywords: evaluation, explicit network, incomplete lineage sorting, simulation. Note: https://dx.doi.org/10.1177%2F1176934317691935.

InProceedings

16 Louigi Addario-Berry, Mike Hallett and Jens Lagergren. Towards Identifying Lateral Gene Transfer Events. In PSB03, 2003. Keywords: evaluation, from rooted trees, from species tree, lateral gene transfer, phylogenetic network, phylogeny, Program LatTrans, reconstruction. Note: http://www.nada.kth.se/~jensl/AHLPsb.pdf.         17 Sergey Bereg and Kathryn Bean. Constructing Phylogenetic Networks from Trees. In BIBE05, Pages 299-305, 2005. 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. 18 Iyad A. Kanj, Luay Nakhleh, Cuong Than and Ge Xia. Seeing the Trees and Their Branches in the Network is Hard. In Proceedings of the Tenth Italian Conference on Theoretical Computer Science (ICTCS'07), 2007. Keywords: evaluation, from network, from rooted trees, NP complete, phylogenetic network, phylogeny, tree containment. Note: http://www.cs.rice.edu/~nakhleh/Papers/ictcs07.pdf.         19 Luay Nakhleh and Li-San Wang. Phylogenetic Networks, Trees, and Clusters. In IWBRA05, Vol. 3515:919-926 of LNCS, springer, 2005. Keywords: cluster containment, evaluation, from clusters, from network, from rooted trees, phylogenetic network, phylogeny, polynomial, tree containment, tree-child network. Note: http://www.cs.rice.edu/~nakhleh/Papers/NakhlehWang.pdf.         20 Luay Nakhleh and Li-San Wang. Phylogenetic Networks: Properties and Relationship to Trees and Clusters. In TCSB2, Vol. 3680:82-99 of LNCS, springer, 2005. Keywords: cluster containment, evaluation, from clusters, from network, from rooted trees, phylogenetic network, phylogeny, polynomial, tree containment, tree-child network. Note: http://www.cs.rice.edu/~nakhleh/Papers/LNCS_TCSB05.pdf.         21 Luay Nakhleh, Jerry Sun, Tandy Warnow, C. Randal Linder, Bernard M. E. Moret and Anna Tholse. Towards the Development of Computational Tools for Evaluating Phylogenetic Network Reconstruction Methods. In PSB03, 2003. Keywords: distance between networks, evaluation, phylogenetic network, phylogeny, polynomial, tripartition distance. Note: http://www.cs.rice.edu/~nakhleh/Papers/psb03.pdf.         22 Patricia Buendia and Giri Narasimhan. Searching for Recombinant Donors in a Phylogenetic Network of Serial Samples. In ISBRA07, Vol. 4463:109-120 of LNCS, springer, 2007. Keywords: evaluation, phylogenetic network, phylogeny, recombination, recombination detection. Note: http://dx.doi.org/10.1007/978-3-540-72031-7_10.         23 Cuong Than and Luay Nakhleh. SPR-based Tree Reconciliation: Non-binary Trees and Multiple Solutions. In APBC08, Pages 251-260, 2008. Keywords: evaluation, from rooted trees, lateral gene transfer, phylogenetic network, phylogeny, Program LatTrans, Program PhyloNet, reconstruction, SPR distance. Note: http://www.cs.rice.edu/~nakhleh/Papers/apbc08.pdf.         24 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.         25 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.

PhdThesis

26 Luay Nakhleh. Phylogenetic Networks. PhD thesis, University of Texas at Austin, U.S.A., 2004. Keywords: distance between networks, evaluation, generation, phylogenetic network, phylogeny, Program SPNet, reconstruction, split, statistical model, tree sibling network. Note: http://www.library.utexas.edu/etd/d/2004/nakhlehl042/nakhlehl042.pdf.         27 Bastienne Vriesendorp. Phylogenenetworks, exploring reticulate evolution and its consequences for phylogenetic reconstruction. PhD thesis, Wageningen University, The Netherlands, 2007. Keywords: consensus, distance between networks, evaluation, hybridization, median network, NeighborNet, parsimony, phylogenetic network, phylogeny, Program SplitsTree, split decomposition, survey. Note: http://library.wur.nl/wda/dissertations/dis4239.pdf.         28 Monique M. Morin. Phylogenetic Networks: Simulation, Characterization, and Reconstruction. PhD thesis, The University of New Mexico, U.S.A., 2007. Keywords: evaluation, explicit network, hybridization, lateral gene transfer, phylogenetic network, phylogeny, Program NetGen, simulation, software. Note: http://www.cs.unm.edu/~morin/morin_phd.pdf.         29 Leo van Iersel. Algorithms, Haplotypes and Phylogenetic Networks. PhD thesis, Eindhoven University of Technology, The Netherlands, 2009. Keywords: evaluation, explicit network, exponential algorithm, FPT, from triplets, galled tree, level k phylogenetic network, mu distance, phylogenetic network, phylogeny, polynomial, Program Level2, Program Marlon, Program Simplistic, Program T REX, reconstruction. Note: http://www.win.tue.nl/~liersel/thesis_vaniersel_viewing.pdf.

Misc

30 Bernard M. E. Moret, Luay Nakhleh and Tandy Warnow. An error metric for phylogenetic networks. 2002. Keywords: distance between networks, evaluation, phylogenetic network, phylogeny, tripartition distance. Note: Technical report TR-02-09, http://www.cs.unm.edu/~treport/tr/03-05/nakhleh.ps.gz.