Evidence map›Paper›PMID 22456957›Full record

ArticleJournal of mathematical biology2013

Orthology relations, symbolic ultrametrics, and cographs.

Marc Hellmuth, Maribel Hernandez-Rosales, Katharina T Huber, Vincent Moulton, Peter F Stadler, Nicolas Wieseke

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Article in Journal of mathematical biology, 2013. 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.

  1. Article
  2. Arboreal networks and their underlying trees.Journal of mathematical biology · 2026
    Article
  3. Orthology and near-cographs in the context of phylogenetic networks.Algorithms for molecular biology : AMB · 2025
    Article
  4. Article
  5. Article
  6. The Theory of Gene Family Histories.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  7. Relative timing information and orthology in evolutionary scenarios.Algorithms for molecular biology : AMB · 2023
    Article
  8. Indirect identification of horizontal gene transfer.Journal of mathematical biology · 2021
    Article
  9. Article
  10. Article
  11. Article
  12. Reciprocal best match graphs.Journal of mathematical biology · 2020
    Article
  13. Reconstruction of time-consistent species trees.Algorithms for molecular biology : AMB · 2020
    Article
  14. Article
  15. Article
  16. Best match graphs.Journal of mathematical biology · 2019
    Article
  17. Reconstructing gene trees from Fitch's xenology relation.Journal of mathematical biology · 2018
    Article
  18. Article
  19. Article
  20. Time-consistent reconciliation maps and forbidden time travel.Algorithms for molecular biology : AMB · 2018
    Article
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

6 authors.

Marc HellmuthCenter for Bioinformatics, Saarland University, Building E 2.1, 66041, Saarbrücken, Germany. marc.hellmuth@bioinf.uni-sb.de
Maribel Hernandez-Rosales
Katharina T Huber
Vincent Moulton
Peter F Stadler
Nicolas Wieseke

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Orthology detection is an important problem in comparative and evolutionary genomics and, consequently, a variety of orthology detection methods have been devised in recent years. Although many of these methods are dependent on generating gene and/or species trees, it has been shown that orthology can be estimated at acceptable levels of accuracy without having to infer gene trees and/or reconciling gene trees with species trees. Thus, it is of interest to understand how much information about the gene tree, the species tree, and their reconciliation is already contained in the orthology relation on the underlying set of genes. Here we shall show that a result by Böcker and Dress concerning symbolic ultrametrics, and subsequent algorithmic results by Semple and Steel for processing these structures can throw a considerable amount of light on this problem. More specifically, building upon these authors' results, we present some new characterizations for symbolic ultrametrics and new algorithms for recovering the associated trees, with an emphasis on how these algorithms could be potentially extended to deal with arbitrary orthology relations. In so doing we shall also show that, somewhat surprisingly, symbolic ultrametrics are very closely related to cographs, graphs that do not contain an induced path on any subset of four vertices. We conclude with a discussion on how our results might be applied in practice to orthology detection.

Indexed as

Models, GeneticPhylogenyAlgorithmsAnimalsComputational BiologyEvolution, MolecularGenomicsHumansMathematical Concepts

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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.