Hierarchies from lowest stable ancestors in nonbinary phylogenetic networks

Huber, Katharina, Moulton, Vincent ORCID: https://orcid.org/0000-0001-9371-6435 and Wu, Taoyang ORCID: https://orcid.org/0000-0002-2663-2001 (2019) Hierarchies from lowest stable ancestors in nonbinary phylogenetic networks. Journal of Classification, 36 (2). pp. 200-231. ISSN 0176-4268

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Abstract

The reconstruction of the evolutionary history of a set of species is an important problem in classification and phylogenetics. Phylogenetic networks are a generalization of evolutionary trees that are used to represent histories for species that have undergone reticulate evolution, an important evolutionary force for many organisms (e.g. plants or viruses). In this paper, we present a novel approach to understanding the structure of networks that are not necessarily binary. More specifically, we define the concept of a closed set and show that the collection of closed sets of a network forms a hierarchy, and that this hierarchy can be deduced from either the subtrees or subnetworks on all 3-subsets. This allows us to also show that closed sets generalize the concept of the SN-sets of a binary network, sets which have proven very useful in elucidating the structure of binary networks. We also characterize the minimal closed sets (under set inclusion) for a special class of networks (2-terminal networks). Taken together, we anticipate that our results should be useful for the development of new phylogenetic network reconstruction algorithms.

Item Type: Article
Uncontrolled Keywords: hierarchy,lower stable ancestor,nonbinary network,phylogenetic network,mathematics (miscellaneous),psychology (miscellaneous),statistics, probability and uncertainty,library and information sciences ,/dk/atira/pure/subjectarea/asjc/2600/2601
Faculty \ School: Faculty of Science > School of Computing Sciences
UEA Research Groups: Faculty of Science > Research Groups > Computational Biology > Phylogenetics (former - to 2018)
Faculty of Science > Research Groups > Computational Biology
Faculty of Science > Research Groups > Computational Biology > Computational biology of RNA (former - to 2018)
Faculty of Science > Research Groups > Norwich Epidemiology Centre
Faculty of Medicine and Health Sciences > Research Groups > Norwich Epidemiology Centre
Related URLs:
Depositing User: Pure Connector
Date Deposited: 20 Oct 2017 05:04
Last Modified: 14 Jun 2023 13:09
URI: https://ueaeprints.uea.ac.uk/id/eprint/65193
DOI: 10.1007/s00357-018-9279-5

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