Ranking Top-k Trees in Tree-Based Phylogenetic Networks

Momoko Hayamizu*, Kazuhisa Makino

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Tree-based phylogenetic networks provide a powerful model for representing complex data or non-tree-like evolution. Such networks consist of an underlying evolutionary tree called a 'support tree' (also known as a 'subdivision tree') together with extra arcs added between the edges of that tree. However, a tree-based network can have exponentially many support trees, and this leads to a variety of computational problems. Recently, Hayamizu established a theory called the structure theorem for rooted binary phylogenetic networks and provided linear-time and linear-delay algorithms for different problems, such as counting, optimization, and enumeration of support trees. However, in practice, it is often more useful to search for both optimal and near-optimal solutions than to calculate only an optimal solution. In the present paper, we thus consider the following problem: Given a tree-based phylogenetic network N where each arc is weighted by its probability, compute the ranking of top-k support trees of N according to their likelihood values. We provide a linear-delay (and hence optimal) algorithm for this problem.

Original languageEnglish
Pages (from-to)2349-2355
Number of pages7
JournalIEEE/ACM Transactions on Computational Biology and Bioinformatics
Issue number3
Publication statusPublished - 2023 May 1


  • Phylogenetic tree
  • algorithm
  • enumeration
  • maximum likelihood estimation
  • spanning tree
  • subdivision tree
  • support tree
  • top-k ranking problem
  • tree-based phylogenetic network

ASJC Scopus subject areas

  • Biotechnology
  • Genetics
  • Applied Mathematics


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