NeighborNet: an agglomerative method for the construction of planar phylogenetic networks

D. Bryant, V. Moulton

Research output: Chapter in Book/Report/Conference proceedingChapter

113 Citations (Scopus)


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(n3) 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.
Original languageEnglish
Title of host publicationAlgorithms in Bioinformatics
EditorsRoderic Guigó, Dan Gusfield
PublisherSpringer Berlin / Heidelberg
Number of pages17
ISBN (Print)978-3-540-44211-0
Publication statusPublished - 2002
EventProceedings of the Second International Workshop - Rome, Italy
Duration: 17 Sep 200221 Sep 2002

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Berlin / Heidelberg


ConferenceProceedings of the Second International Workshop

Cite this