Evidence map›Paper›PMID 41029411›Full record

ArticleGenome biology2025

Jiadong Mao, Yidi Deng, Kim-Anh Lê Cao

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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Genome biology · 2025
    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

3 authors.

Jiadong MaoMelbourne Integrative Genomics, School of Mathematics and Statistics, The University of Melbourne, Parkville, 3010, Victoria, Australia.
Yidi DengMelbourne Integrative Genomics, School of Mathematics and Statistics, The University of Melbourne, Parkville, 3010, Victoria, Australia.
Kim-Anh Lê CaoMelbourne Integrative Genomics, School of Mathematics and Statistics, The University of Melbourne, Parkville, 3010, Victoria, Australia. kimanh.lecao@unimelb.edu.au.

Funding

Australian Research Council DP200102903National Health and Medical Research Council GNT2025648
6 · The paper itself

Abstract

The prevalence of single-cell multi-omics datasets calls for automated cell type annotation methods that can characterize novel cell states. We developed

Indexed as

Computational BiologyGenomicsPhenotypeSingle-Cell AnalysisHumansMultiomicsSoftwareCell type annotationMulti-omicsReference mappingSingle-cell

Identifiers

PMID41029411
PMCPMC12482742

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.