Evidence map›Paper›PMID 28289571›Full record

ArticlePeerJ2017

Differential bicodon usage in lowly and highly abundant proteins.

Luis A Diambra

Abstract read
In one paragraph

Article in PeerJ, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
  2. Article
  3. Influence of Nucleophosmin (Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2025
    Article
  4. Article
  5. Article
  6. Article
  7. Dicodon-based measures for modeling gene expression.Bioinformatics (Oxford, England) · 2023
    Article
  8. Distal nucleotides affect the rate of stop codon read-through.Quantitative biology (Beijing, China) · 2023
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. COSMO: A dynamic programming algorithm for multicriteria codon optimization.Computational and structural biotechnology journal · 2020
    Article
  15. Article
  16. Article
  17. Article
  18. Review
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.

Luis A DiambraCentro Regional de Estudios Genómicos, Universidad Nacional de La Plata, CONICET , La Plata , Argentina.ORCID 0000-0001-8052-4880

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Degeneracy in the genetic code implies that different codons can encode the same amino acid. Usage preference of synonymous codons has been observed in all domains of life. There is much evidence suggesting that this bias has a major role on protein elongation rate, contributing to differential expression and to co-translational folding. In addition to codon usage bias, other preference variations have been observed such as codon pairs. In this paper, I report that codon pairs have significant different frequency usage for coding either lowly or highly abundant proteins. These usage preferences cannot be explained by the frequency usage of the single codons. The statistical analysis of coding sequences of nine organisms reveals that in many cases bicodon preferences are shared between related organisms. Furthermore, it is observed that misfolding in the drug-transport protein, encoded by

Indexed as

Codon pairsCo-translational foldingSynonymous codon usageTranslational rate

Identifiers

PMID28289571
PMCPMC5346287

What OpenQuestion holds

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Registered trials

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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.