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

Elizabeth Gross, Leo van Iersel, Remie Janssen, Mark Jones, Colby Long, Yukihiro Murakami

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)
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Phylogenetic networks can represent evolutionary events that cannot be described by phylogenetic trees. These networks are able to incorporate reticulate evolutionary events such as hybridization, introgression, and lateral gene transfer. Recently, network-based Markov models of DNA sequence evolution have been introduced along with model-based methods for reconstructing phylogenetic networks. For these methods to be consistent, the network parameter needs to be identifiable from data generated under the model. Here, we show that the semi-directed network parameter of a triangle-free, level-1 network model with any fixed number of reticulation vertices is generically identifiable under the Jukes–Cantor, Kimura 2-parameter, or Kimura 3-parameter constraints.

Original languageEnglish
Article number32
Pages (from-to)1-24
Number of pages24
JournalJournal of Mathematical Biology
Issue number3
Publication statusPublished - 2021


  • Identifiability
  • Markov processes
  • Phylogenetic networks
  • Reticulation


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