Evidence map›Paper›PMID 23841456›Full record

ArticleBMC evolutionary biology2013

EGN: a wizard for construction of gene and genome similarity networks.

Sébastien Halary, James O McInerney, Philippe Lopez, Eric Bapteste

Open access · goldAbstract read
In one paragraph

Article in BMC evolutionary biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
2.7field-weighted citation impact, top 10% of its field
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

34 citing papers in PubMed, 58 citations in OpenAlex.

  1. Comparative genomics betweenFrontiers in microbiology · 2024
    Article
  2. Evolutionary conservation ofFrontiers in microbiology · 2023
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. Review
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

4 authors at 3 institutions in 4 countries.

Sébastien HalaryDépartement de sciences biologiques, Institut de recherche en biologie végétale (IRBV), Université de Montréal, Montréal, QC H1X 2B2, Canada. sebastien.halary@umontreal.ca
James O McInerney
Philippe Lopez
Eric Bapteste
Centre National pour la Recherche Scientifique et Technique (CNRST) · MANational University of Ireland, Maynooth · IEUniversité de Montréal · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIncreasingly, similarity networks are being used for evolutionary analyses of molecular datasets. These networks are very useful, in particular for the analysis of gene sharing, lateral gene transfer and for the detection of distant homologs. Currently, such analyses require some computer programming skills due to the limited availability of user-friendly freely distributed software. Consequently, although appealing, the construction and analyses of these networks remain less familiar to biologists than do phylogenetic approaches.

resultsIn order to ease the use of similarity networks in the community of evolutionary biologists, we introduce a software program, EGN, that runs under Linux or MacOSX. EGN automates the reconstruction of gene and genome networks from nucleic and proteic sequences. EGN also implements statistics describing genetic diversity in these samples, for various user-defined thresholds of similarities. In the interest of studying the complexity of evolutionary processes affecting microbial evolution, we applied EGN to a dataset of 571,044 proteic sequences from the three domains of life and from mobile elements. We observed that, in Borrelia, plasmids play a different role than in most other eubacteria. Rather than being genetic couriers involved in lateral gene transfer, Borrelia's plasmids and their genes act as private genetic goods, that contribute to the creation of genetic diversity within their parasitic hosts.

conclusionEGN can be used for constructing, analyzing, and mining molecular datasets in evolutionary studies. The program can help increase our knowledge of the processes through which genes from distinct sources and/or from multiple genomes co-evolve in lineages of cellular organisms.

Indexed as

Gene Regulatory NetworksGenome, BacterialSoftwareBorreliaEvolution, MolecularGenetic VariationGene Transfer, HorizontalPlasmids

Identifiers

PMID23841456
PMCPMC3727994
OpenAlexW1997608219

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.