Evidence map›Paper›PMID 28258183›Full record

ArticleGenetics2017

The Bacterial Sequential Markov Coalescent.

Nicola De Maio, Daniel J Wilson

Open access · bronzeAbstract read
In one paragraph

Article in Genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

15 citing papers in PubMed, 32 citations in OpenAlex.

  1. Article
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  7. VGsim: scalable viral genealogy simulator for global pandemic.medRxiv : the preprint server for health sciences · 2021
    Article
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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 at 1 institution in 1 country.

Nicola De MaioInstitute for Emerging Infections, Oxford Martin School, University of Oxford, Oxford, OX1 3PA, United Kingdom nicola.de.maio.85@gmail.com nicola.demaio@ndm.ox.ac.uk.ORCID 0000-0002-1776-8564
Daniel J WilsonInstitute for Emerging Infections, Oxford Martin School, University of Oxford, Oxford, OX1 3PA, United Kingdom.
University of Oxford · GB

Funding

Wellcome TrustWellcome Trust 101237/Z/13/Z
6 · The paper itself

Abstract

Bacteria can exchange and acquire new genetic material from other organisms directly and via the environment. This process, known as bacterial recombination, has a strong impact on the evolution of bacteria, for example, leading to the spread of antibiotic resistance across clades and species, and to the avoidance of clonal interference. Recombination hinders phylogenetic and transmission inference because it creates patterns of substitutions (homoplasies) inconsistent with the hypothesis of a single evolutionary tree. Bacterial recombination is typically modeled as statistically akin to gene conversion in eukaryotes,

Indexed as

Genetics, PopulationRecombination, GeneticAlgorithmsBacteriaBayes TheoremComputer SimulationGene ConversionGenome, BacterialLinkage DisequilibriumMarkov ChainsModels, GeneticSoftwareABCbacterial evolutioncoalescentrecombinationsimulations

Identifiers

PMID28258183
PMCPMC5419479
OpenAlexW2953324318

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.