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Updated: Aug 26, 2025

A Practical Guide to Phylogenetics for Nonexperts
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Phylogenetic tree reconstruction via graph cut presented using a quantum-inspired computer.

Wataru Onodera1, Nobuyuki Hara2, Shiho Aoki1

  • 1Faculty of Science and Engineering, Waseda University, TWIns, 2-2 Wakamatsu, Shinjuku, Tokyo 162-8480, Japan.

Molecular Phylogenetics and Evolution
|October 8, 2022
PubMed
Summary

A new method, Normalized-Minimum cut by Digital Annealer (NMcutDA), uses quantum-inspired computing to optimize graph cuts for reconstructing accurate phylogenetic trees, especially for highly diverged sequences.

Keywords:
Distance-matrix methodGraph cutPhylogenetic reconstructionQuantum-inspired computing

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Area of Science:

  • Evolutionary biology
  • Bioinformatics
  • Computational biology

Background:

  • Phylogenetic trees are crucial for understanding evolutionary relationships.
  • Reconstructing accurate phylogenetic trees is computationally challenging due to the vast number of possible topologies.
  • Existing graph cut methods for phylogenetic tree reconstruction often rely on approximations.

Purpose of the Study:

  • To develop an improved method for phylogenetic tree reconstruction using quantum-inspired computing.
  • To optimize the graph cut process for enhanced accuracy in phylogenetic analysis.
  • To introduce the Normalized-Minimum cut by Digital Annealer (NMcutDA) method.

Main Methods:

  • Utilized a quantum-inspired computer, the Fujitsu Digital Annealer (DA).
  • Developed the Normalized-Minimum cut by Digital Annealer (NMcutDA) algorithm.
  • Compared the normalized cut value criterion with existing clustering methods.
  • Applied NMcutDA to simulated and real-world protein sequence data.

Main Results:

  • NMcutDA demonstrated superior accuracy in reconstructing phylogenetic trees, particularly for diverged sequences.
  • The method successfully clustered protein sequences into correct superfamilies using real data.
  • NMcutDA outperformed other methods in optimizing graph cuts for phylogenetic reconstruction.

Conclusions:

  • NMcutDA offers a more accurate and efficient approach to phylogenetic tree reconstruction.
  • The method shows significant promise for analyzing highly diverged biological sequences.
  • Quantum-inspired computing can advance phylogenetic analysis and evolutionary biology research.