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In the light of deep coalescence: revisiting trees within networks
by
Zhu, Jiafan
, Nakhleh, Luay
, Yu, Yun
in
Algorithms
/ Bioinformatics
/ Biological Evolution
/ Biomedical and Life Sciences
/ Computational Biology/Bioinformatics
/ Computer Appl. in Life Sciences
/ Life Sciences
/ Microarrays
/ Models, Genetic
/ Phylogenetic trees
/ Phylogeny
2016
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In the light of deep coalescence: revisiting trees within networks
by
Zhu, Jiafan
, Nakhleh, Luay
, Yu, Yun
in
Algorithms
/ Bioinformatics
/ Biological Evolution
/ Biomedical and Life Sciences
/ Computational Biology/Bioinformatics
/ Computer Appl. in Life Sciences
/ Life Sciences
/ Microarrays
/ Models, Genetic
/ Phylogenetic trees
/ Phylogeny
2016
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Do you wish to request the book?
In the light of deep coalescence: revisiting trees within networks
by
Zhu, Jiafan
, Nakhleh, Luay
, Yu, Yun
in
Algorithms
/ Bioinformatics
/ Biological Evolution
/ Biomedical and Life Sciences
/ Computational Biology/Bioinformatics
/ Computer Appl. in Life Sciences
/ Life Sciences
/ Microarrays
/ Models, Genetic
/ Phylogenetic trees
/ Phylogeny
2016
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In the light of deep coalescence: revisiting trees within networks
Journal Article
In the light of deep coalescence: revisiting trees within networks
2016
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Overview
Background
Phylogenetic networks model reticulate evolutionary histories. The last two decades have seen an increased interest in establishing mathematical results and developing computational methods for inferring and analyzing these networks. A salient concept underlying a great majority of these developments has been the notion that a network displays a set of trees and those trees can be used to infer, analyze, and study the network.
Results
In this paper, we show that in the presence of coalescence effects, the set of displayed trees is not sufficient to capture the network. We formally define the set of parental trees of a network and make three contributions based on this definition. First, we extend the notion of anomaly zone to phylogenetic networks and report on anomaly results for different networks. Second, we demonstrate how coalescence events could negatively affect the ability to infer a species tree that could be augmented into the correct network. Third, we demonstrate how a phylogenetic network can be viewed as a mixture model that lends itself to a novel inference approach via gene tree clustering.
Conclusions
Our results demonstrate the limitations of focusing on the set of trees displayed by a network when analyzing and inferring the network. Our findings can form the basis for achieving higher accuracy when inferring phylogenetic networks and open up new venues for research in this area, including new problem formulations based on the notion of a network’s parental trees.
Publisher
BioMed Central,BioMed Central Ltd
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