Agreement Subtree Mapping Kernel for Phylogenetic Trees

  • Issei Hamada
  • Takaharu Shimada
  • Daiki Nakata
  • Kouichi Hirata
  • Tetsuji Kuboyama
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8417)


In this paper, we introduce an agreement subtree mapping kernel counting all of the agreement subtree mappings and design the algorithm to compute it for phylogenetic trees, which are unordered leaf-labeled full binary trees, in quadratic time. Then, by applying the agreement subtree mapping kernel to trimmed phylogenetic trees obtained from all the positions in nucleotide sequences for A (H1N1) influenza viruses, we classify pandemic viruses from non-pandemic viruses and viruses in one region from viruses in the other regions. On the other hand, for leaf-labeled trees, we show that the problem of counting all of the agreement subtree mappings is #P-complete.


Nucleotide Sequence Phylogenetic Tree Rooted Tree Internal Node Quadratic Time 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Issei Hamada
    • 1
  • Takaharu Shimada
    • 1
    • 4
  • Daiki Nakata
    • 1
  • Kouichi Hirata
    • 2
  • Tetsuji Kuboyama
    • 3
  1. 1.Graduate School of Computer Science and Systems EngineeringKyushu Institute of TechnologyIizukaJapan
  2. 2.Department of Artificial IntelligenceKyushu Institute of TechnologyIizukaJapan
  3. 3.Computer CenterGakushuin UniversityToshimaJapan
  4. 4.Mazda Motor CorporationHiroshimaJapan

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