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Encoding and Constructing 1-Nested Phylogenetic Networks with Trinets

2011/10/04 by Katharina T. Huber, K. T. Huber, Huber, K. T. +3
Agricultural and Biological Sciences · Biochemistry, Genetics and Molecular Biology · Computer Science · Earth and Planetary Sciences · #05C05 #68R05 #92D15 #Data Structures and Algorithms (cs.DS) #Evolution and Paleontology Studies #FOS: Biological sciences #FOS: Computer and information sciences #Genomics and Phylogenetic Studies #Plant Diversity and Evolution #Populations and Evolution (q-bio.PE) #cs.DS #msc:05C05 #msc:68R05 #msc:92D15 #q-bio.PE

paper · pdf · doi:10.48550/arxiv.1110.0728

arxiv created 2011/10/04 · openalex publication_date 2011/10/04 · arxiv updated 2011/10/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Phylogenetic networks are a generalization of phylogenetic trees that are used in biology to represent reticulate or non-treelike evolution. Recently, several algorithms have been developed which aim to construct phylogenetic networks from biological data using \em triplets, i.e. binary phylogenetic trees on 3-element subsets of a given set of species. However, a fundamental problem with this approach is that the triplets displayed by a phylogenetic network do not necessary uniquely determine or \em encode the network. Here we propose an alternative approach to encoding and constructing phylogenetic networks, which uses phylogenetic networks on 3-element subsets of a set, or \em trinets, rather than triplets. More specifically, we show that for a special, well-studied type of phylogenetic network called a 1-nested network, the trinets displayed by a 1-nested network always encode the network. We also present an efficient algorithm for deciding whether a \em dense set of trinets (i.e. one that contains a trinet on every 3-element subset of a set) can be displayed by a 1-nested network or not and, if so, constructs that network. In addition, we discuss some potential new directions that this new approach opens up for constructing and comparing phylogenetic networks.

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