ArticlePLoS computational biology2015
Reconstructible phylogenetic networks: do not distinguish the indistinguishable.
Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 38 papers.
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Who cites it
38 citing papers in PubMed, 90 citations in OpenAlex.
- PhyloZoo: a unified framework for phylogenetic network analysis in Python.Bioinformatics (Oxford, England) · 2026Article
- Phylotranscriptomics Allows Distinguishing Major Gene Flow Events from Incomplete Lineage Sorting in Rapidly Diversifying Mimetic Orchids (Genus Ophrys).Genome biology and evolution · 2026Article
- Phylogenetic networks empower biodiversity research.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Reading tree leaves: inferring speciation anfd extinction processes using phylogenies.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025Review
- Simplifying and Characterizing DAGs and Phylogenetic Networks via Least Common Ancestor Constraints.Bulletin of mathematical biology · 2025Article
- Detection of Ghost Introgression Requires Exploiting Topological and Branch Length Information.Systematic biology · 2024Article
- Introgression Underlies Phylogenetic Uncertainty But Not Parallel Plumage Evolution in a Recent Songbird Radiation.Systematic biology · 2024Article
- Constructing phylogenetic networks via cherry picking and machine learning.Algorithms for molecular biology : AMB · 2023Article
- Phylogenomics reveals widespread hybridization and polyploidization in Henckelia (Gesneriaceae).Annals of botany · 2023Article
- Autopolyploidy, Allopolyploidy, and Phylogenetic Networks with Horizontal Arcs.Bulletin of mathematical biology · 2023Article
- A complete theoretical framework for inferring horizontal gene transfers using partial order sets.PloS one · 2023Article
- New taxonomic framework for Arthrodermataceae: a comprehensive analysis based on their phylogenetic reconstruction, divergence time estimation, phylogenetic split network, and phylogeography.Antonie van Leeuwenhoek · 2022Article
- NetRAX: accurate and fast maximum likelihood phylogenetic network inference.Bioinformatics (Oxford, England) · 2022Article
- Classes of explicit phylogenetic networks and their biological and mathematical significance.Journal of mathematical biology · 2022Review
- Estimation of Cross-Species Introgression Rates Using Genomic Data Despite Model Unidentifiability.Molecular biology and evolution · 2022Article
- Candidate-species delimitation inEcology and evolution · 2022Article
- Merging Arcs to Produce Acyclic Phylogenetic Networks and Normal Networks.Bulletin of mathematical biology · 2022Article
- Multispecies coalescent and its applications to infer species phylogenies and cross-species gene flow.National science review · 2021Article
- Distinguishing level-1 phylogenetic networks on the basis of data generated by Markov processes.Journal of mathematical biology · 2021Article
- On the inference of complex phylogenetic networks by Markov Chain Monte-Carlo.PLoS computational biology · 2021Article
Corrections and comments
- Erratum issued
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Phylogenetic networks represent the evolution of organisms that have undergone reticulate events, such as recombination, hybrid speciation or lateral gene transfer. An important way to interpret a phylogenetic network is in terms of the trees it displays, which represent all the possible histories of the characters carried by the organisms in the network. Interestingly, however, different networks may display exactly the same set of trees, an observation that poses a problem for network reconstruction: from the perspective of many inference methods such networks are "indistinguishable". This is true for all methods that evaluate a phylogenetic network solely on the basis of how well the displayed trees fit the available data, including all methods based on input data consisting of clades, triples, quartets, or trees with any number of taxa, and also sequence-based approaches such as popular formalisations of maximum parsimony and maximum likelihood for networks. This identifiability problem is partially solved by accounting for branch lengths, although this merely reduces the frequency of the problem. Here we propose that network inference methods should only attempt to reconstruct what they can uniquely identify. To this end, we introduce a novel definition of what constitutes a uniquely reconstructible network. For any given set of indistinguishable networks, we define a canonical network that, under mild assumptions, is unique and thus representative of the entire set. Given data that underwent reticulate evolution, only the canonical form of the underlying phylogenetic network can be uniquely reconstructed. While on the methodological side this will imply a drastic reduction of the solution space in network inference, for the study of reticulate evolution this is a fundamental limitation that will require an important change of perspective when interpreting phylogenetic networks.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.