Evidence map›Paper›PMID 26774999›Full record

ReviewTrends in microbiology2016

Network-Thinking: Graphs to Analyze Microbial Complexity and Evolution.

Eduardo Corel, Philippe Lopez, Raphaël Méheust, Eric Bapteste

Abstract readReview
In one paragraph

Review in Trends in microbiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing 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

48 citing papers in PubMed.

  1. Article
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  4. Challenges in Assembling the Dated Tree of Life.Genome biology and evolution · 2024
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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

4 authors.

Eduardo CorelEquipe AIRE, UMR 7138, Laboratoire Evolution Paris-Seine, Université Pierre et Marie Curie, 7 quai St Bernard 75005 Paris, France. Electronic address: eduardo.corel@upmc.fr.
Philippe LopezEquipe AIRE, UMR 7138, Laboratoire Evolution Paris-Seine, Université Pierre et Marie Curie, 7 quai St Bernard 75005 Paris, France.
Raphaël MéheustEquipe AIRE, UMR 7138, Laboratoire Evolution Paris-Seine, Université Pierre et Marie Curie, 7 quai St Bernard 75005 Paris, France.
Eric BaptesteEquipe AIRE, UMR 7138, Laboratoire Evolution Paris-Seine, Université Pierre et Marie Curie, 7 quai St Bernard 75005 Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The tree model and tree-based methods have played a major, fruitful role in evolutionary studies. However, with the increasing realization of the quantitative and qualitative importance of reticulate evolutionary processes, affecting all levels of biological organization, complementary network-based models and methods are now flourishing, inviting evolutionary biology to experience a network-thinking era. We show how relatively recent comers in this field of study, that is, sequence-similarity networks, genome networks, and gene families-genomes bipartite graphs, already allow for a significantly enhanced usage of molecular datasets in comparative studies. Analyses of these networks provide tools for tackling a multitude of complex phenomena, including the evolution of gene transfer, composite genes and genomes, evolutionary transitions, and holobionts.

Indexed as

Evolution, MolecularGene Regulatory NetworksModels, GeneticBacteriaGene Transfer, HorizontalGenomeSymbiosisbipartite graphevolutiongene transfergraph theoryintrogressionsymbiosis

Identifiers

PMID26774999
PMCPMC4766943

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.