Evidence map›Paper›PMID 23979428›Full record

ReviewNature reviews. Microbiology2013

MLST revisited: the gene-by-gene approach to bacterial genomics.

Martin C J Maiden, Melissa J Jansen van Rensburg, James E Bray, Sarah G Earle, Suzanne A Ford, Keith A Jolley, Noel D McCarthy

Abstract readReview
In one paragraph

Review in Nature reviews. Microbiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 430 papers.

0numbers the graph read from it
0cells of the map it votes in
430citing 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

430 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Multidrug-resistant avian pathogenicVeterinary and animal science · 2026
    Article
  6. Article
  7. Phenotypic, Genetic, and Virulence Characterization ofPathogens (Basel, Switzerland) · 2026
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Strain-level analyses of public sequencing data to characterizeOne health (Amsterdam, Netherlands) · 2026
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Decoding the genome of Bacillus thuringiensis subsp. israelensis VCRC B668 to understand its mosquitocidal potential for biopesticide development.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2026
    Article
  19. Article
  20. Article

370 more citing papers are in PubMed but not listed here.

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

7 authors.

Martin C J MaidenDepartment of Zoology, University of Oxford, South Parks Road, Oxford OX1 3PS, UK.
Melissa J Jansen van Rensburg
James E Bray
Sarah G Earle
Suzanne A Ford
Keith A Jolley
Noel D McCarthy

Funding

Wellcome Trust 087622
6 · The paper itself

Abstract

Multilocus sequence typing (MLST) was proposed in 1998 as a portable sequence-based method for identifying clonal relationships among bacteria. Today, in the whole-genome era of microbiology, the need for systematic, standardized descriptions of bacterial genotypic variation remains a priority. Here, to meet this need, we draw on the successes of MLST and 16S rRNA gene sequencing to propose a hierarchical gene-by-gene approach that reflects functional and evolutionary relationships and catalogues bacteria 'from domain to strain'. Our gene-based typing approach using online platforms such as the Bacterial Isolate Genome Sequence Database (BIGSdb) allows the scalable organization and analysis of whole-genome sequence data.

Indexed as

Genome, BacterialAllelesBacteriaBacterial Typing TechniquesBase SequenceDatabases, GeneticEvolution, MolecularGenetic VariationGenomicsMultilocus Sequence TypingRNA, BacterialRNA, Ribosomal, 16SRNA, BacterialRNA, Ribosomal, 16S

Identifiers

PMID23979428
PMCPMC3980634

What OpenQuestion holds

Textmetadata
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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.