NeighborNet: improved algorithms and implementation
NeighborNet constructs phylogenetic networks to visualize distance data. It is a popular method used in a wide range of applications. While several studies have investigated its mathematical features, here we focus on computational aspects. The algorithm operates in three steps. We present a new sim...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2023-09-01
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| Series: | Frontiers in Bioinformatics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fbinf.2023.1178600/full |
| _version_ | 1797679236857724928 |
|---|---|
| author | David Bryant Daniel H. Huson Daniel H. Huson |
| author_facet | David Bryant Daniel H. Huson Daniel H. Huson |
| author_sort | David Bryant |
| collection | DOAJ |
| description | NeighborNet constructs phylogenetic networks to visualize distance data. It is a popular method used in a wide range of applications. While several studies have investigated its mathematical features, here we focus on computational aspects. The algorithm operates in three steps. We present a new simplified formulation of the first step, which aims at computing a circular ordering. We provide the first technical description of the second step, the estimation of split weights. We review the third step by constructing and drawing the network. Finally, we discuss how the networks might best be interpreted, review related approaches, and present some open questions. |
| first_indexed | 2024-03-11T23:11:35Z |
| format | Article |
| id | doaj.art-81877778bf944a3b8120ab51e85aedc2 |
| institution | Directory Open Access Journal |
| issn | 2673-7647 |
| language | English |
| last_indexed | 2024-03-11T23:11:35Z |
| publishDate | 2023-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Bioinformatics |
| spelling | doaj.art-81877778bf944a3b8120ab51e85aedc22023-09-21T08:36:59ZengFrontiers Media S.A.Frontiers in Bioinformatics2673-76472023-09-01310.3389/fbinf.2023.11786001178600NeighborNet: improved algorithms and implementationDavid Bryant0Daniel H. Huson1Daniel H. Huson2Department of Mathematics and Statistics, University of Otago, Dunedin, New ZealandAlgorithms in Bioinformatics, University of Tübingen, Tübingen, GermanyCluster of Excellence: Controlling Microbes to Fight Infection, University of Tübingen, Tübingen, GermanyNeighborNet constructs phylogenetic networks to visualize distance data. It is a popular method used in a wide range of applications. While several studies have investigated its mathematical features, here we focus on computational aspects. The algorithm operates in three steps. We present a new simplified formulation of the first step, which aims at computing a circular ordering. We provide the first technical description of the second step, the estimation of split weights. We review the third step by constructing and drawing the network. Finally, we discuss how the networks might best be interpreted, review related approaches, and present some open questions.https://www.frontiersin.org/articles/10.3389/fbinf.2023.1178600/fullNeighborNetphylogenetic networksSplitsTreesplit networksplanar graph drawing |
| spellingShingle | David Bryant Daniel H. Huson Daniel H. Huson NeighborNet: improved algorithms and implementation Frontiers in Bioinformatics NeighborNet phylogenetic networks SplitsTree split networks planar graph drawing |
| title | NeighborNet: improved algorithms and implementation |
| title_full | NeighborNet: improved algorithms and implementation |
| title_fullStr | NeighborNet: improved algorithms and implementation |
| title_full_unstemmed | NeighborNet: improved algorithms and implementation |
| title_short | NeighborNet: improved algorithms and implementation |
| title_sort | neighbornet improved algorithms and implementation |
| topic | NeighborNet phylogenetic networks SplitsTree split networks planar graph drawing |
| url | https://www.frontiersin.org/articles/10.3389/fbinf.2023.1178600/full |
| work_keys_str_mv | AT davidbryant neighbornetimprovedalgorithmsandimplementation AT danielhhuson neighbornetimprovedalgorithmsandimplementation AT danielhhuson neighbornetimprovedalgorithmsandimplementation |