Who is Who in Phylogenetic Networks

Publications related to 'Program LNetwork' : LNetwork is a Java program which takes as input a set of rooted phylogenetic trees in the Newick format and outputs a rooted phylogenetic networks in the extended Newick format. Available at http://nclab.hit.edu.cn/~wangjuan/LNETWORK/   Order by:   Type | Year

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Associated keywords

evaluation explicit-network from-clusters from-rooted-trees heuristic phylogenetic-network phylogeny Program-BIMLR Program-Dendroscope Program-IGNet Program-LNetwork Program-QuickCass reconstruction software survey

2019

1 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.

2016

2 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.

2014

3 Juan Wang. A new algorithm to construct phylogenetic networks from trees. In Genetics and Molecular Research, Vol. 13(1):1456-1464, 2014. Keywords: explicit network, from clusters, heuristic, phylogenetic network, Program LNetwork, Program QuickCass, reconstruction. Note: http://dx.doi.org/10.4238/2014.March.6.4.         Toggle abstract "Developing appropriate methods for constructing phylogenetic networks from tree sets is an important problem, and much research is currently being undertaken in this area. BIMLR is an algorithm that constructs phylogenetic networks from tree sets. The algorithm can construct a much simpler network than other available methods. Here, we introduce an improved version of the BIMLR algorithm, QuickCass. QuickCass changes the selection strategy of the labels of leaves below the reticulate nodes, i.e., the nodes with an indegree of at least 2 in BIMLR. We show that QuickCass can construct simpler phylogenetic networks than BIMLR. Furthermore, we show that QuickCass is a polynomial-time algorithm when the output network that is constructed by QuickCass is binary. © FUNPEC-RP."

2013

4 Juan Wang, Maozu Guo, Xiaoyan Liu, Yang Liu, Chunyu Wang, Linlin Xing and Kai Che. LNETWORK: An Efficient and Effective Method for Constructing Phylogenetic Networks. In BIO, Vol. 29(18):2269-2276, 2013. Keywords: explicit network, from rooted trees, phylogenetic network, phylogeny, Program LNetwork, reconstruction, software.         Toggle abstract "Motivation: The evolutionary history of species is traditionally represented with a rooted phylogenetic tree. Each tree comprises a set of clusters, i.e. subsets of the species that are descended from a common ancestor. When rooted phylogenetic trees are built from several different datasets (e.g. from different genes), the clusters are often conflicting. These conflicting clusters cannot be expressed as a simple phylogenetic tree; however, they can be expressed in a phylogenetic network. Phylogenetic networks are a generalization of phylogenetic trees that can account for processes such as hybridization, horizontal gene transfer and recombination, which are difficult to represent in standard tree-like models of evolutionary histories. There is currently a large body of research aimed at developing appropriate methods for constructing phylogenetic networks from cluster sets. The Cass algorithm can construct a much simpler network than other available methods, but is extremely slow for large datasets or for datasets that need lots of reticulate nodes. The networks constructed by Cass are also greatly dependent on the order of input data, i.e. it generally derives different phylogenetic networks for the same dataset when different input orders are used.Results: In this study, we introduce an improved Cass algorithm, Lnetwork, which can construct a phylogenetic network for a given set of clusters. We show that Lnetwork is significantly faster than Cass and effectively weakens the influence of input data order. Moreover, we show that Lnetwork can construct a much simpler network than most of the other available methods. © The Author 2013."