Literature DB >> 16447967

Reconstructing phylogenetic networks using maximum parsimony.

Luay Nakhleh1, Guohua Jin, Fengmei Zhao, John Mellor-Crummey.   

Abstract

Phylogenies - the evolutionary histories of groups of organisms - are one of the most widely used tools throughout the life sciences, as well as objects of research within systematics, evolutionary biology, epidemiology, etc. Almost every tool devised to date to reconstruct phylogenies produces trees; yet it is widely understood and accepted that trees oversimplify the evolutionary histories of many groups of organims, most prominently bacteria (because of horizontal gene transfer) and plants (because of hybrid speciation). Various methods and criteria have been introduced for phylogenetic tree reconstruction. Parsimony is one of the most widely used and studied criteria, and various accurate and efficient heuristics for reconstructing trees based on parsimony have been devised. Jotun Hein suggested a straightforward extension of the parsimony criterion to phylogenetic networks. In this paper we formalize this concept, and provide the first experimental study of the quality of parsimony as a criterion for constructing and evaluating phylogenetic networks. Our results show that, when extended to phylogenetic networks, the parsimony criterion produces promising results. In a great majority of the cases in our experiments, the parsimony criterion accurately predicts the numbers and placements of non-tree events.

Mesh:

Year:  2005        PMID: 16447967     DOI: 10.1109/csb.2005.47

Source DB:  PubMed          Journal:  Proc IEEE Comput Syst Bioinform Conf        ISSN: 1551-7497


  11 in total

1.  Network Analysis of Sequence-Function Relationships and Exploration of Sequence Space of TEM β-Lactamases.

Authors:  Catharina Zeil; Michael Widmann; Silvia Fademrecht; Constantin Vogel; Jürgen Pleiss
Journal:  Antimicrob Agents Chemother       Date:  2016-04-22       Impact factor: 5.191

2.  Exactly computing the parsimony scores on phylogenetic networks using dynamic programming.

Authors:  Lavanya Kannan; Ward C Wheeler
Journal:  J Comput Biol       Date:  2014-02-21       Impact factor: 1.479

3.  Treewidth-based algorithms for the small parsimony problem on networks.

Authors:  Celine Scornavacca; Mathias Weller
Journal:  Algorithms Mol Biol       Date:  2022-08-20       Impact factor: 1.721

4.  Bootstrap-based support of HGT inferred by maximum parsimony.

Authors:  Hyun Jung Park; Guohua Jin; Luay Nakhleh
Journal:  BMC Evol Biol       Date:  2010-05-05       Impact factor: 3.260

5.  Maximum Parsimony on Phylogenetic networks.

Authors:  Lavanya Kannan; Ward C Wheeler
Journal:  Algorithms Mol Biol       Date:  2012-05-02       Impact factor: 1.405

6.  In the light of deep coalescence: revisiting trees within networks.

Authors:  Jiafan Zhu; Yun Yu; Luay Nakhleh
Journal:  BMC Bioinformatics       Date:  2016-11-11       Impact factor: 3.169

7.  Finding a most parsimonious or likely tree in a network with respect to an alignment.

Authors:  Steven Kelk; Fabio Pardi; Celine Scornavacca; Leo van Iersel
Journal:  J Math Biol       Date:  2018-08-19       Impact factor: 2.259

8.  PhyloNet: a software package for analyzing and reconstructing reticulate evolutionary relationships.

Authors:  Cuong Than; Derek Ruths; Luay Nakhleh
Journal:  BMC Bioinformatics       Date:  2008-07-28       Impact factor: 3.169

9.  Phylogenetic network analysis as a parsimony optimization problem.

Authors:  Ward C Wheeler
Journal:  BMC Bioinformatics       Date:  2015-09-17       Impact factor: 3.169

10.  Protein variants form a system of networks: microdiversity of IMP metallo-beta-lactamases.

Authors:  Michael Widmann; Jürgen Pleiss
Journal:  PLoS One       Date:  2014-07-11       Impact factor: 3.240

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