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Scanning Phylogenetic Networks Is NP-hard

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SOFSEM 2020: Theory and Practice of Computer Science (SOFSEM 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12011))

Abstract

Phylogenetic networks are rooted directed acyclic graphs used to depict the evolution of a set of species in the presence of reticulate events. Reconstructing these networks from molecular data is challenging and current algorithms fail to scale up to genome-wide data. In this paper, we introduce a new width measure intended to help design faster parameterized algorithms for this task. We study its relation with other width measures and problems in graph theory and finally prove that deciding it is NP-complete, even for very restricted classes of networks.

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Acknowledgments

We thank Fabio Pardi to have brought the problem to our attention and the Genome Harvest project, ref. ID 1504-006 (“Investissements d’avenir”, ANR-10-LABX-0001-01).

Author information

Authors and Affiliations

  1. LIRMM, Université de Montpellier, Montpellier, France

    Vincent Berry

  2. CNRS, Université de Montpellier, Montpellier, France

    Celine Scornavacca

  3. CNRS, LIGM, Université Paris Est, Marne-la-Vallée, France

    Mathias Weller

Authors
  1. Vincent Berry
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  2. Celine Scornavacca
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  3. Mathias Weller
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Corresponding author

Correspondence to Mathias Weller .

Editor information

Editors and Affiliations

  1. University of Macedonia, Thessaloniki, Greece

    Alexander Chatzigeorgiou

  2. University of Bergamo, Bergamo, Italy

    Riccardo Dondi

  3. Cyprus University of Technology, Limassol, Cyprus

    Herodotos Herodotou

  4. Carnegie Mellon University Qatar, Doha, Qatar

    Christos Kapoutsis

  5. Open University of Cyprus, Nicosia, Cyprus

    Yannis Manolopoulos

  6. University of Cyprus, Nicosia, Cyprus

    George A. Papadopoulos

  7. Paris Dauphine University, Paris, France

    Florian Sikora

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Berry, V., Scornavacca, C., Weller, M. (2020). Scanning Phylogenetic Networks Is NP-hard. In: Chatzigeorgiou, A., et al. SOFSEM 2020: Theory and Practice of Computer Science. SOFSEM 2020. Lecture Notes in Computer Science(), vol 12011. Springer, Cham. https://doi.org/10.1007/978-3-030-38919-2_42

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  • DOI: https://doi.org/10.1007/978-3-030-38919-2_42

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-38918-5

  • Online ISBN: 978-3-030-38919-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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