NeighborNet: improved algorithms and implementation

Frontiers in Bioinformatics

Bioinformatics

Daniel H. Huson¹  David Bryant² 

[1] Algorithms in Bioinformatics, University of Tübingen, Tübingen, Germany;Cluster of Excellence: Controlling Microbes to Fight Infection, University of Tübingen, Tübingen, Germany;Department of Mathematics and Statistics, University of Otago, Dunedin, New Zealand;

关键词: NeighborNet;    phylogenetic networks;    SplitsTree;    split networks;    planar graph drawing;   

DOI  :  10.3389/fbinf.2023.1178600

 received in 2023-03-03, accepted in 2023-08-04,  发布年份 2023

来源: Frontiers

【 摘 要 】

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.

【 授权许可】

Unknown   
Copyright © 2023 Bryant and Huson.