Literature DB >> 29272537

Improved Maximum Parsimony Models for Phylogenetic Networks.

Leo Van Iersel1, Mark Jones1, Celine Scornavacca2,3.   

Abstract

Phylogenetic networks are well suited to represent evolutionary histories comprising reticulate evolution. Several methods aiming at reconstructing explicit phylogenetic networks have been developed in the last two decades. In this article, we propose a new definition of maximum parsimony for phylogenetic networks that permits to model biological scenarios that cannot be modeled by the definitions currently present in the literature (namely, the "hardwired" and "softwired" parsimony). Building on this new definition, we provide several algorithmic results that lay the foundations for new parsimony-based methods for phylogenetic network reconstruction.

Mesh:

Year:  2018        PMID: 29272537     DOI: 10.1093/sysbio/syx094

Source DB:  PubMed          Journal:  Syst Biol        ISSN: 1063-5157            Impact factor:   15.683


  3 in total

1.  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

2.  Embedding gene trees into phylogenetic networks by conflict resolution algorithms.

Authors:  Marcin Wawerka; Dawid Dąbkowski; Natalia Rutecka; Agnieszka Mykowiecka; Paweł Górecki
Journal:  Algorithms Mol Biol       Date:  2022-05-19       Impact factor: 1.721

3.  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

  3 in total

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