Literature DB >> 21393651

A practical algorithm for reconstructing level-1 phylogenetic networks.

Katharina T Huber1, Leo van Iersel, Steven Kelk, Radosław Suchecki.   

Abstract

Recently, much attention has been devoted to the construction of phylogenetic networks which generalize phylogenetic trees in order to accommodate complex evolutionary processes. Here, we present an efficient, practical algorithm for reconstructing level-1 phylogenetic networks--a type of network slightly more general than a phylogenetic tree--from triplets. Our algorithm has been made publicly available as the program LEV1ATHAN. It combines ideas from several known theoretical algorithms for phylogenetic tree and network reconstruction with two novel subroutines. Namely, an exponential-time exact and a greedy algorithm both of which are of independent theoretical interest. Most importantly, LEV1ATHAN runs in polynomial time and always constructs a level-1 network. If the data are consistent with a phylogenetic tree, then the algorithm constructs such a tree. Moreover, if the input triplet set is dense and, in addition, is fully consistent with some level-1 network, it will find such a network. The potential of LEV1ATHAN is explored by means of an extensive simulation study and a biological data set. One of our conclusions is that LEV1ATHAN is able to construct networks consistent with a high percentage of input triplets, even when these input triplets are affected by a low to moderate level of noise.

Mesh:

Year:  2011        PMID: 21393651     DOI: 10.1109/TCBB.2010.17

Source DB:  PubMed          Journal:  IEEE/ACM Trans Comput Biol Bioinform        ISSN: 1545-5963            Impact factor:   3.710


  9 in total

1.  Determining phylogenetic networks from inter-taxa distances.

Authors:  Magnus Bordewich; Charles Semple
Journal:  J Math Biol       Date:  2015-12-14       Impact factor: 2.259

2.  Spaces of phylogenetic networks from generalized nearest-neighbor interchange operations.

Authors:  Katharina T Huber; Simone Linz; Vincent Moulton; Taoyang Wu
Journal:  J Math Biol       Date:  2015-06-03       Impact factor: 2.259

3.  Reconstruction of LGT networks from tri-LGT-nets.

Authors:  Gabriel Cardona; Joan Carles Pons
Journal:  J Math Biol       Date:  2017-04-27       Impact factor: 2.259

4.  Trinets encode tree-child and level-2 phylogenetic networks.

Authors:  Leo van Iersel; Vincent Moulton
Journal:  J Math Biol       Date:  2013-05-17       Impact factor: 2.259

5.  On the challenge of reconstructing level-1 phylogenetic networks from triplets and clusters.

Authors:  Philippe Gambette; K T Huber; S Kelk
Journal:  J Math Biol       Date:  2016-10-31       Impact factor: 2.259

6.  Distinguishing level-1 phylogenetic networks on the basis of data generated by Markov processes.

Authors:  Elizabeth Gross; Leo van Iersel; Remie Janssen; Mark Jones; Colby Long; Yukihiro Murakami
Journal:  J Math Biol       Date:  2021-09-04       Impact factor: 2.259

7.  TripNet: a method for constructing rooted phylogenetic networks from rooted triplets.

Authors:  Hadi Poormohammadi; Changiz Eslahchi; Ruzbeh Tusserkani
Journal:  PLoS One       Date:  2014-09-10       Impact factor: 3.240

8.  How much information is needed to infer reticulate evolutionary histories?

Authors:  Katharina T Huber; Leo Van Iersel; Vincent Moulton; Taoyang Wu
Journal:  Syst Biol       Date:  2014-09-18       Impact factor: 15.683

9.  Netcombin: An algorithm for constructing optimal phylogenetic network from rooted triplets.

Authors:  Hadi Poormohammadi; Mohsen Sardari Zarchi
Journal:  PLoS One       Date:  2020-09-18       Impact factor: 3.240

  9 in total

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