Evidence map›Paper›PMID 40001217›Full record

ArticleGenome biology2025

De novo basecalling of RNA modifications at single molecule and nucleotide resolution.

Sonia Cruciani, Anna Delgado-Tejedor, Leszek P Pryszcz, Rebeca Medina, Laia Llovera, Eva Maria Novoa

Abstract read
In one paragraph

Article in Genome biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing 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

36 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Single-molecule mbioRxiv : the preprint server for biology · 2026
    Article
  5. Article
  6. Epitranscriptomic Analysis of A-to-I RNA Editing and mInternational journal of molecular sciences · 2026
    Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. NanoCortex: A Unified Agentic System for Nanopore Sequencing Analysis.bioRxiv : the preprint server for biology · 2026
    Article
  14. Emerging roles of non-mNature plants · 2026
    Review
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. 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

6 authors.

Sonia Cruciani *Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona, 08003, Spain.
Anna Delgado-Tejedor *Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona, 08003, Spain.
Leszek P Pryszcz *Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona, 08003, Spain. lpryszcz@crg.eu.
Rebeca MedinaCentre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona, 08003, Spain.
Laia LloveraCentre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona, 08003, Spain.
Eva Maria NovoaCentre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona, 08003, Spain. eva.novoa@crg.eu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RNA modifications influence RNA function and fate, but detecting them in individual molecules remains challenging for most modifications. Here we present a novel methodology to generate training sets and build modification-aware basecalling models. Using this approach, we develop the m

Indexed as

RNARNA Processing, Post-TranscriptionalAdenosineHumansAdenosineRNABasecallingMachine learningN6-methyladenosineNanopore sequencingNative RNARNA modificationsSingle molecule resolutionTraining data

Identifiers

PMID40001217
PMCPMC11853310

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.