Evidence map›Paper›PMID 21685078›Full record

ArticleBioinformatics (Oxford, England)2011

Tanglegrams for rooted phylogenetic trees and networks.

Celine Scornavacca, Franziska Zickmann, Daniel H Huson

Abstract read
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Article in Bioinformatics (Oxford, England), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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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

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3 · Its place in the literature

Who cites it

44 citing papers in PubMed.

  1. Article
  2. Displacement-Optimized Tanglegrams for Trees and Networks.Molecular biology and evolution · 2026
    Article
  3. Article
  4. A Pandemic-Scale Ancestral Recombination Graph for SARS-CoV-2.bioRxiv : the preprint server for biology · 2025
    Article
  5. Article
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  7. Article
  8. Article
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  10. Article
  11. Frontiers in microbiology · 2023
    Article
  12. Article
  13. Article
  14. A vectorial tree distance measure.Scientific reports · 2022
    Article
  15. Article
  16. Article
  17. Article
  18. Article
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4 · The record

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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

3 authors.

Celine ScornavaccaCenter for Bioinformatics (ZBIT), Tübingen University, Sand 14, 72076 Tübingen, Germany. scornava@informatik.uni-tuebingen.de
Franziska Zickmann
Daniel H Huson

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationIn systematic biology, one is often faced with the task of comparing different phylogenetic trees, in particular in multi-gene analysis or cospeciation studies. One approach is to use a tanglegram in which two rooted phylogenetic trees are drawn opposite each other, using auxiliary lines to connect matching taxa. There is an increasing interest in using rooted phylogenetic networks to represent evolutionary history, so as to explicitly represent reticulate events, such as horizontal gene transfer, hybridization or reassortment. Thus, the question arises how to define and compute a tanglegram for such networks.

resultsIn this article, we present the first formal definition of a tanglegram for rooted phylogenetic networks and present a heuristic approach for computing one, called the NN-tanglegram method. We compare the performance of our method with existing tree tanglegram algorithms and also show a typical application to real biological datasets. For maximum usability, the algorithm does not require that the trees or networks are bifurcating or bicombining, or that they are on identical taxon sets. AVAILABILITY: The algorithm is implemented in our program Dendroscope 3, which is freely available from www.dendroscope.org. CONTACT: scornava@informatik.uni-tuebingen.de; huson@informatik.uni-tuebingen.de.

Indexed as

Biological EvolutionPhylogenyAlgorithmsAnimalsBiologyComputational BiologyComputer SimulationFicusGene Transfer, HorizontalHybridization, GeneticWasps

Identifiers

PMID21685078
PMCPMC3117342

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LicenceCC BY-NC
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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.