Reconstructing k-Reticulated Phylogenetic Network from a Set of Gene Trees

  • Hoa Vu
  • Francis Chin
  • W. K. Hon
  • Henry Leung
  • K. Sadakane
  • Ken W. K. Sung
  • Siu-Ming Yiu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7875)

Abstract

The time complexity of existing algorithms for reconstructing a level-x phylogenetic network increases exponentially in x. In this paper, we propose a new classification of phylogenetic networks called k-reticulated network. A k-reticulated network can model all level-k networks and some level-x networks with x > k. We design algorithms for reconstructing k-reticulated network (k = 1 or 2) with minimum number of hybrid nodes from a set of m binary trees, each with n leaves in O(mn2) time. The implication is that some level-x networks with x > k can now be reconstructed in a faster way. We implemented our algorithm (ARTNET) and compared it with CMPT. We show that ARTNET outperforms CMPT in terms of running time and accuracy. We also consider the case when there does not exist a 2-reticulated network for the input trees. We present an algorithm computing a maximum subset of the species set so that a new set of subtrees can be combined into a 2-reticulated network.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Hoa Vu
    • 1
  • Francis Chin
    • 1
  • W. K. Hon
    • 2
  • Henry Leung
    • 1
  • K. Sadakane
    • 3
  • Ken W. K. Sung
    • 4
  • Siu-Ming Yiu
    • 1
  1. 1.Department of Computer ScienceThe University of Hong KongHong Kong
  2. 2.Department of Computer ScienceNational Tsinghua UniversityTaiwan
  3. 3.Informatics Research DivisionNational Institute of InformaticsJapan
  4. 4.Department of Computer ScienceNational University of SingaporeSingapore

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