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Bryant, David and Moulton, Vincent 
ORCID: https://orcid.org/0000-0001-9371-6435
(2002)
NeighborNet: an agglomerative method for the construction of planar phylogenetic networks.
In:
Algorithms in Bioinformatics.
Lecture Notes in Computer Science, 2452
.
Springer Berlin / Heidelberg, ITA, pp. 375-391.
ISBN 978-3-540-44211-0
Abstract
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.
| Item Type: | Book Section |
|---|---|
| Faculty \ School: | Faculty of Science > School of Computing Sciences |
| UEA Research Groups: | Faculty of Science > Research Groups > Norwich Epidemiology Centre Faculty of Medicine and Health Sciences > Research Groups > Norwich Epidemiology Centre Faculty of Science > Research Groups > Computational Biology Faculty of Science > Research Groups > Computational Biology > Computational biology of RNA (former - to 2018) Faculty of Science > Research Groups > Computational Biology > Phylogenetics (former - to 2018) |
| Related URLs: | |
| Depositing User: | Vishal Gautam |
| Date Deposited: | 27 Jul 2011 12:21 |
| Last Modified: | 16 Jun 2023 07:31 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/21612 |
| DOI: | 10.1007/3-540-45784-4_28 |
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