Who is Who in Phylogenetic Networks

Publications related to 'Program ConsensusNetwork' : Available at http://www.info2.uqam.ca/~makarenkov_v/ConsensusNetwork.rar   Order by:   Type | Year

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explicit-network from-rooted-trees from-species-tree phylogenetic-network phylogeny Program-ConsensusNetwork reconstruction

Article (Journal)

1 Mehdi Layeghifard, Pedro R. Peres-Neto and Vladimir Makarenkov. Inferring explicit weighted consensus networks to represent alternative evolutionary histories. In BMCEB, Vol. 13(274):1-25, 2013. Keywords: explicit network, from rooted trees, from species tree, phylogenetic network, phylogeny, Program ConsensusNetwork, reconstruction. Note: http://dx.doi.org/10.1186/1471-2148-13-274.         Toggle abstract "Background: The advent of molecular biology techniques and constant increase in availability of genetic material have triggered the development of many phylogenetic tree inference methods. However, several reticulate evolution processes, such as horizontal gene transfer and hybridization, have been shown to blur the species evolutionary history by causing discordance among phylogenies inferred from different genes. Methods. To tackle this problem, we hereby describe a new method for inferring and representing alternative (reticulate) evolutionary histories of species as an explicit weighted consensus network which can be constructed from a collection of gene trees with or without prior knowledge of the species phylogeny. Results: We provide a way of building a weighted phylogenetic network for each of the following reticulation mechanisms: diploid hybridization, intragenic recombination and complete or partial horizontal gene transfer. We successfully tested our method on some synthetic and real datasets to infer the above-mentioned evolutionary events which may have influenced the evolution of many species. Conclusions: Our weighted consensus network inference method allows one to infer, visualize and validate statistically major conflicting signals induced by the mechanisms of reticulate evolution. The results provided by the new method can be used to represent the inferred conflicting signals by means of explicit and easy-to-interpret phylogenetic networks. © 2013 Layeghifard et al.; licensee BioMed Central Ltd."