Abstract
In evolutionary biology, phylogenetic networks are constructed to represent the evolution of species in which reticulate events are thought to have occurred, such as recombination and hybridization. It is therefore useful to have efficiently computable metrics with which to systematically compare such networks. Through developing an optimal algorithm to enumerate all trinets displayed by a level-1 network (a type of network that is slightly more general than an evolutionary tree), here we propose a cubic-time algorithm to compute the trinet distance between two level-1 networks. Employing simulations, we also present a comparison between the trinet metric and the so-called Robinson-Foulds phylogenetic network metric restricted to level-1 networks. The algorithms described in this paper have been implemented in JAVA and are freely available at (https://www.uea.ac.uk/computing/TriLoNet)
Original language | English |
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Pages (from-to) | 36–41 |
Number of pages | 6 |
Journal | Information Processing Letters |
Volume | 123 |
Early online date | 16 Mar 2017 |
DOIs | |
Publication status | Published - Jul 2017 |
Keywords
- Phylogenetic tree
- Phylogenetic network
- Level-1 network
- Trinet
- Robinson-Foulds metric
Profiles
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Vincent Moulton
- School of Computing Sciences - Professor in Computational Biology
- Norwich Epidemiology Centre - Member
- Computational Biology - Member
Person: Research Group Member, Academic, Teaching & Research
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Taoyang Wu
- School of Computing Sciences - Lecturer in Computing Sciences
- Centre for Ecology, Evolution and Conservation - Member
- Computational Biology - Member
Person: Research Group Member, Research Centre Member, Academic, Teaching & Research