Evidence map›Paper›PMID 37799982›Full record

ArticleFrontiers in bioinformatics2023

NeighborNet: improved algorithms and implementation.

David Bryant, Daniel H Huson

Abstract read
In one paragraph

Article in Frontiers in bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

31 citing papers in PubMed.

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  12. Repeated losses of self-fertility shaped heterozygosity and polyploidy in yeast evolution.Proceedings of the National Academy of Sciences of the United States of America · 2026
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  14. IMA fungus · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

David Bryant *Department of Mathematics and Statistics, University of Otago, Dunedin, New Zealand.
Daniel H Huson *Algorithms in Bioinformatics, University of Tübingen, Tübingen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

NeighborNetphylogenetic networksplanar graph drawingsplit networksSplitsTree

Identifiers

PMID37799982
PMCPMC10548196

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.