Evidence map›Paper›PMID 32274012›Full record

ArticleF1000Research2019

Ali Mostafa Anwar, Mohamed Soudy, Radwa Mohamed

Abstract read
In one paragraph

Article in F1000Research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Bipartite Genomes inInternational journal of molecular sciences · 2023
    Article
  9. Article
  10. Article
  11. Article
  12. Microbial genomics · 2021
    Article
  13. Article
  14. Article
  15. Article
  16. Deciphering the co-adaptation of codon usage between respiratory coronaviruses and their human host uncovers candidate therapeutics for COVID-19.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2020
    Article
  17. F1000Research · 2019
    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

3 authors.

Ali Mostafa AnwarDepartment of Genetics, Faculty of Agriculture, Cairo University, Cairo, 12613, Egypt.
Mohamed SoudyBioinformatics program, Faculty of Computer Science, Ain Shams University, Ain Shams, Egypt.
Radwa MohamedDepartment of Genetics, Faculty of Agriculture, Cairo University, Cairo, 12613, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Viruses show noticeable evolution to adapt and reproduce within their hosts. Theoretically, patterns and factors that affect the codon usage of viruses should reflect evolutionary changes that allow them to optimize their codon usage to their hosts. Some software tools can analyze the codon usage of organisms; however, their performance has room for improvement, as these tools do not focus on examining the codon usage co-adaptation between viruses and their hosts. This paper describes the

Indexed as

Codon UsageGenome, ViralVirusesCodonEvolution, MolecularCodonAdaptationCodon Usage BiasEvolutionNatural selectionRRStudioViruses

Identifiers

PMID32274012
PMCPMC7104870

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.