NeighborNet: An Agglomerative Method for the Construction of Planar Phylogenetic Networks

  • David Bryant
  • Vincent Moulton
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2452)


We introduce NeighborNet, a network construction and data representation method that combines aspects of the neighbor joining (NJ) and SplitsTree. Like NJ, NeighborNet uses agglomeration: taxa are combined into progressively larger and larger overlapping clusters. Like SplitsTree, NeighborNet constructs networks rather than trees, and so can be used to represent multiple phylogenetic hypotheses simultaneously, or to detect complex evolutionary processes like recombination, lateral transfer and hybridization. NeighborNet tends to produce networks that are substantially more resolved than those made with SplitsTree. The method is efficient (O(n 3) time) and is well suited for the preliminary analyses of complex phylogenetic data. We report results of three case studies: one based on mitochondrial gene order data from early branching eukaryotes, another based on nuclear sequence data from New Zealand alpine buttercups (Ranunculi), and a third on poorly corrected synthetic data.


Networks Phylogenetics Hybridization SplitsTree Neighbor-Joining 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • David Bryant
    • 1
  • Vincent Moulton
    • 2
  1. 1.McGill Centre for Bioinformatics3775 University St, MontréalQuébec
  2. 2.Linnaeus Center for BioinformaticsUppsala UniversityUppsalaSweden

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