Evidence map›Paper›PMID 36266445›Full record

ReviewExperimental & molecular medicine2022

Detection technologies for RNA modifications.

Yan Zhang, Liang Lu, Xiaoyu Li

Abstract readReview
In one paragraph

Review in Experimental & molecular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 106 papers.

0numbers the graph read from it
0cells of the map it votes in
106citing 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

106 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Compendium of RNA modifications for bacterial stress adaptation.Microbiology and molecular biology reviews : MMBR · 2026
    Review
  6. Review
  7. Review
  8. Article
  9. Article
  10. Ψ-Atlas: An Integrated Atlas for Pseudouridine Epitranscriptome.Genomics, proteomics & bioinformatics · 2026
    Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Review
  16. Article
  17. Pseudouridylation landscape across 42bioRxiv : the preprint server for biology · 2026
    Article
  18. Review
  19. Review
  20. Article

46 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

3 authors.

Yan ZhangDepartment of Biochemistry and Department of Gastroenterology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China.
Liang LuDepartment of Biochemistry and Department of Gastroenterology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China.
Xiaoyu LiDepartment of Biochemistry and Department of Gastroenterology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China. xiaoyu_li@zju.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To date, more than 170 chemical modifications have been characterized in RNA, providing a new layer of gene expression regulation termed the 'epitranscriptome'. RNA modification detection methods and tools advance the functional studies of the epitranscriptome. According to the detection throughput and principles, existing RNA modification detection technologies can be categorized into four classes, including quantification methods, locus-specific detection methods, next-generation sequencing-based detection technologies and nanopore direct RNA sequencing-based technologies. In this review, we summarize the current knowledge about these RNA modification detection technologies and discuss the challenges for the existing detection tools, providing information for a comprehensive understanding of the epitranscriptome.

Indexed as

High-Throughput Nucleotide SequencingRNAGene Expression RegulationSequence Analysis, RNARNA

Identifiers

PMID36266445
PMCPMC9636272

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.