Evidence map›Paper›PMID 38528499›Full record

ArticleBMC bioinformatics2024

m6A-TCPred: a web server to predict tissue-conserved human m

Gang Tu, Xuan Wang, Rong Xia, Bowen Song

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.0field-weighted citation impact, top 8% 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

12 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. mArXiv · 2026
    Article
  3. Systematic identification of tissue-conserved mbioRxiv : the preprint server for biology · 2026
    Article
  4. Article
  5. Article
  6. Functional Prediction of Epitranscriptome.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  7. Exploring the methyl-verse: Dynamic interplay of epigenome and m6A epitranscriptome.Molecular therapy : the journal of the American Society of Gene Therapy · 2025
    Review
  8. Review
  9. Hybrid representation learning for human mBioinformatics advances · 2025
    Article
  10. Article
  11. Review
  12. 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

4 authors at 2 institutions in 1 country.

Gang TuDepartment of Biological Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, 215123, China.
Xuan WangDepartment of Biological Sciences, Xi'an Jiaotong-Liverpool University, Suzhou, 215123, China. xuan.wang@liverpool.ac.uk.
Rong XiaDepartment of Financial and Actuarial Mathematics, Xi'an Jiaotong-Liverpool University, Suzhou, 215123, China.
Bowen SongDepartment of Public Health, School of Medicine, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
Xi’an Jiaotong-Liverpool University · CNNanjing University of Chinese Medicine · CN

Funding

Scientific Research Foundation of Nanjing University of Chinese Medicine 013038030001XJTLU Key Program Special Fund KSF-E-51 and KSF-P-02
6 · The paper itself

Abstract

backgroundN6-methyladenosine (m

resultsWe report here m6A-TCPred, a computational tool for predicting tissue-conserved m

conclusionOur results have been integrated into an online platform: a database holding 268,115 high confidence m

Indexed as

AdenosineComputersHumansMachine LearningRNA Processing, Post-TranscriptionalAdenosineN-methyladenosineGene ontologym6A modificationMachine learningSupport vector machineWeb server

Identifiers

PMID38528499
PMCPMC10962094
OpenAlexW4393157770

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.