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Close lower and upper bounds for the minimum reticulate network of multiple phylogenetic trees

Motivation: Reticulate network is a model for displaying and quantifying the effects of complex reticulate processes on the evolutionary history of species undergoing reticulate evolution. A central computational problem on reticulate networks is: given a set of phylogenetic trees (each for some reg...

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Autor principal: Wu, Yufeng
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2881383/
https://www.ncbi.nlm.nih.gov/pubmed/20529899
http://dx.doi.org/10.1093/bioinformatics/btq198
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author Wu, Yufeng
author_facet Wu, Yufeng
author_sort Wu, Yufeng
collection PubMed
description Motivation: Reticulate network is a model for displaying and quantifying the effects of complex reticulate processes on the evolutionary history of species undergoing reticulate evolution. A central computational problem on reticulate networks is: given a set of phylogenetic trees (each for some region of the genomes), reconstruct the most parsimonious reticulate network (called the minimum reticulate network) that combines the topological information contained in the given trees. This problem is well-known to be NP-hard. Thus, existing approaches for this problem either work with only two input trees or make simplifying topological assumptions. Results: We present novel results on the minimum reticulate network problem. Unlike existing approaches, we address the fully general problem: there is no restriction on the number of trees that are input, and there is no restriction on the form of the allowed reticulate network. We present lower and upper bounds on the minimum number of reticulation events in the minimum reticulate network (and infer an approximately parsimonious reticulate network). A program called PIRN implements these methods, which also outputs a graphical representation of the inferred network. Empirical results on simulated and biological data show that our methods are practical for a wide range of data. More importantly, the lower and upper bounds match for many datasets (especially when the number of trees is small or reticulation level is low), and this allows us to solve the minimum reticulate network problem exactly for these datasets. Availability: A software tool, PIRN, is available for download from the web page: http://www.engr.uconn.edu/~ywu. Contact: ywu@engr.uconn.edu Supplementary information: Supplementary data is available at Bioinformatics online.
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spelling pubmed-28813832010-06-08 Close lower and upper bounds for the minimum reticulate network of multiple phylogenetic trees Wu, Yufeng Bioinformatics Ismb 2010 Conference Proceedings July 11 to July 13, 2010, Boston, Ma, Usa Motivation: Reticulate network is a model for displaying and quantifying the effects of complex reticulate processes on the evolutionary history of species undergoing reticulate evolution. A central computational problem on reticulate networks is: given a set of phylogenetic trees (each for some region of the genomes), reconstruct the most parsimonious reticulate network (called the minimum reticulate network) that combines the topological information contained in the given trees. This problem is well-known to be NP-hard. Thus, existing approaches for this problem either work with only two input trees or make simplifying topological assumptions. Results: We present novel results on the minimum reticulate network problem. Unlike existing approaches, we address the fully general problem: there is no restriction on the number of trees that are input, and there is no restriction on the form of the allowed reticulate network. We present lower and upper bounds on the minimum number of reticulation events in the minimum reticulate network (and infer an approximately parsimonious reticulate network). A program called PIRN implements these methods, which also outputs a graphical representation of the inferred network. Empirical results on simulated and biological data show that our methods are practical for a wide range of data. More importantly, the lower and upper bounds match for many datasets (especially when the number of trees is small or reticulation level is low), and this allows us to solve the minimum reticulate network problem exactly for these datasets. Availability: A software tool, PIRN, is available for download from the web page: http://www.engr.uconn.edu/~ywu. Contact: ywu@engr.uconn.edu Supplementary information: Supplementary data is available at Bioinformatics online. Oxford University Press 2010-06-15 2010-06-01 /pmc/articles/PMC2881383/ /pubmed/20529899 http://dx.doi.org/10.1093/bioinformatics/btq198 Text en © The Author(s) 2010. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Ismb 2010 Conference Proceedings July 11 to July 13, 2010, Boston, Ma, Usa
Wu, Yufeng
Close lower and upper bounds for the minimum reticulate network of multiple phylogenetic trees
title Close lower and upper bounds for the minimum reticulate network of multiple phylogenetic trees
title_full Close lower and upper bounds for the minimum reticulate network of multiple phylogenetic trees
title_fullStr Close lower and upper bounds for the minimum reticulate network of multiple phylogenetic trees
title_full_unstemmed Close lower and upper bounds for the minimum reticulate network of multiple phylogenetic trees
title_short Close lower and upper bounds for the minimum reticulate network of multiple phylogenetic trees
title_sort close lower and upper bounds for the minimum reticulate network of multiple phylogenetic trees
topic Ismb 2010 Conference Proceedings July 11 to July 13, 2010, Boston, Ma, Usa
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2881383/
https://www.ncbi.nlm.nih.gov/pubmed/20529899
http://dx.doi.org/10.1093/bioinformatics/btq198
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