Evidence map›Paper›PMID 19765997›Full record

ReviewTrends in microbiology2009

Bacteriophages as model organisms for virus emergence research.

John J Dennehy

Open access · bronzeAbstract readReview
In one paragraph

Review in Trends in microbiology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed, 41 citations in OpenAlex.

  1. Nicking Activity of M13 Bacteriophage Protein 2.International journal of molecular sciences · 2025
    Article
  2. Article
  3. Article
  4. Article
  5. Evolutionary ecology of virus emergence.Annals of the New York Academy of Sciences · 2017
    Review
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. What limits the evolutionary emergence of pathogens?Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2013
    Article
  13. Review
  14. Article
  15. Article
  16. What Can Phages Tell Us about Host-Pathogen Coevolution?International journal of evolutionary biology · 2012
    Article
  17. Article
  18. Risk factors for the evolutionary emergence of pathogens.Journal of the Royal Society, Interface · 2010
    Article
  19. Combining mathematics and empirical data to predict emergence of RNA viruses that differ in reservoir use.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2010
    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

1 author at 1 institution in 1 country.

John J DennehyDepartment of Biology, Queens College and the Graduate Center of the City University of New York, 65-30 Kissena Blvd., Flushing, NY 11367, USA. jdennehy@gmail.com
The Graduate Center, CUNY · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Viruses fully emerge by gaining the ability to sustainably infect new host populations. When the hosts are humans, emerging viruses can present major public health issues, as exemplified by the AIDS pandemic. Therefore, heuristic approaches to identify nascent diseases before they become pandemic would be valuable. Unfortunately, the current patient-based and epidemiological approaches are ill-suited in this regard because they are largely responsive and not predictive. Alternative approaches based on virus evolutionary ecology might have greater potential to predict virus emergence. However, given the difficulties encountered when studying metazoan viruses in this context, the development of new model systems is greatly desirable. Here, I highlight studies that show that bacteriophages are appropriate model organisms for virus emergence research because of the ease in which important population parameters can be manipulated. Ideally this research will permit identifying major factors determining the persistence or extinction of emerging viruses. If such viruses could be recognized in advance, patient-based and epidemiological strategies could be better mobilized to deal with them.

Indexed as

EcosystemEvolution, MolecularBacteriaBacteriophagesModels, BiologicalModels, TheoreticalVirus Diseases

Identifiers

PMID19765997
PMCPMC7127698
OpenAlexW2034548473

What OpenQuestion holds

Textmetadata
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.