Evidence map›Paper›PMID 36382183›Full record

ReviewComputational and structural biotechnology journal2022

Detecting RNA modification using direct RNA sequencing: A systematic review.

Xichen Zhao, Yuxin Zhang, Daiyun Hang, Jia Meng, Zhen Wei

Open access · goldAbstract readReview
In one paragraph

Review in Computational and structural biotechnology journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
2.5field-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

20 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.

  1. Systematic review and meta-analysis of bulk RNAseq studies in human Alzheimer's disease brain tissue.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    Pooled it
  2. Compendium of RNA modifications for bacterial stress adaptation.Microbiology and molecular biology reviews : MMBR · 2026
    Review
  3. Epitranscriptomic Analysis of A-to-I RNA Editing and mInternational journal of molecular sciences · 2026
    Review
  4. Review
  5. Article
  6. Review
  7. Review
  8. Review
  9. Review
  10. Article
  11. Epitranscriptomic alterations induced by environmental toxins: implications for RNA modifications and disease.Genes and environment : the official journal of the Japanese Environmental Mutagen Society · 2025
    Review
  12. Review
  13. Article
  14. Article
  15. RNA modifications and their role in gene expression.Frontiers in molecular biosciences · 2025
    Review
  16. Article
  17. Article
  18. Review
  19. Article
  20. Current Insights into mPlants (Basel, Switzerland) · 2023
    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

5 authors at 2 institutions in 3 countries.

Xichen ZhaoDepartment of Biological Sciences, Xi'an Jiaotong-Liverpool University, 215123 Suzhou, Jiangsu, China.
Yuxin ZhangDepartment of Biological Sciences, Xi'an Jiaotong-Liverpool University, 215123 Suzhou, Jiangsu, China.
Daiyun HangDepartment of Biological Sciences, Xi'an Jiaotong-Liverpool University, 215123 Suzhou, Jiangsu, China.
Jia MengDepartment of Biological Sciences, Xi'an Jiaotong-Liverpool University, 215123 Suzhou, Jiangsu, China.
Zhen WeiDepartment of Biological Sciences, Xi'an Jiaotong-Liverpool University, 215123 Suzhou, Jiangsu, China.
University of Liverpool · GBXi’an Jiaotong-Liverpool University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Post-transcriptional RNA modifications are involved in a range of important cellular processes, including the regulation of gene expression and fine-tuning of the functions of RNA molecules. To decipher the context-specific functions of these post-transcriptional modifications, it is crucial to accurately determine their transcriptomic locations and modification levels under a given cellular condition. With the newly emerged sequencing technology, especially nanopore direct RNA sequencing, different RNA modifications can be detected simultaneously with a single molecular level resolution. Here we provide a systematic review of 15 published RNA modification prediction tools based on direct RNA sequencing data, including their computational models, input-output formats, supported modification types, and reported performances. Finally, we also discussed the potential challenges and future improvements of nanopore sequencing-based methods for RNA modification detection.

Identifiers

PMID36382183
PMCPMC9619219
OpenAlexW4306970980

What Socratic 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 Socratic graph.