Evidence map›Paper›PMID 40234030›Full record

ArticleGenome research2025

Integrating genetic variation with deep learning provides context for variants impacting transcription factor binding during embryogenesis.

Olga M Sigalova, Mattia Forneris, Frosina Stojanovska, Bingqing Zhao, Rebecca R Viales, Adam Rabinowitz, Fayrouz Hammal, Benoît Ballester, Judith B Zaugg, Eileen E M Furlong

Abstract read
In one paragraph

Article in Genome research, 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. ModelingbioRxiv : the preprint server for biology · 2026
    Article
  3. 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

10 authors.

Olga M Sigalova *European Molecular Biology Laboratory (EMBL), Genome Biology Unit, D-69117 Heidelberg, Germany.ORCID 0000-0001-8598-1079
Mattia Forneris *European Molecular Biology Laboratory (EMBL), Genome Biology Unit, D-69117 Heidelberg, Germany.ORCID 0000-0002-2126-9207
Frosina StojanovskaEuropean Molecular Biology Laboratory (EMBL), Structural and Computational Biology Unit, D-69117 Heidelberg, Germany.ORCID 0000-0002-4327-1068
Bingqing ZhaoEuropean Molecular Biology Laboratory (EMBL), Genome Biology Unit, D-69117 Heidelberg, Germany.ORCID 0000-0001-5000-7436
Rebecca R VialesEuropean Molecular Biology Laboratory (EMBL), Genome Biology Unit, D-69117 Heidelberg, Germany.ORCID 0000-0003-3739-7438
Adam RabinowitzEuropean Molecular Biology Laboratory (EMBL), Genome Biology Unit, D-69117 Heidelberg, Germany.ORCID 0000-0003-3853-6196
Fayrouz HammalAix Marseille Univ, INSERM, TAGC, 13009 Marseille, France.ORCID 0000-0002-7612-4953
Benoît BallesterAix Marseille Univ, INSERM, TAGC, 13009 Marseille, France.ORCID 0000-0002-0834-7135
Judith B ZauggEuropean Molecular Biology Laboratory (EMBL), Structural and Computational Biology Unit, D-69117 Heidelberg, Germany; judith.zaugg@embl.de furlong@embl.de.ORCID 0000-0001-8324-4040
Eileen E M FurlongEuropean Molecular Biology Laboratory (EMBL), Genome Biology Unit, D-69117 Heidelberg, Germany; judith.zaugg@embl.de furlong@embl.de.ORCID 0000-0002-9544-8339

Funding

European Research Council 787611
6 · The paper itself

Abstract

Understanding how genetic variation impacts transcription factor (TF) binding remains a major challenge, limiting our ability to model disease-associated variants. Here, we used a highly controlled system of F

Indexed as

Deep LearningDrosophila ProteinsEmbryonic DevelopmentGenetic VariationTranscription FactorsAllelesAnimalsBinding SitesDrosophilaDrosophila melanogasterProtein BindingDrosophila ProteinsTranscription Factors

Identifiers

PMID40234030
PMCPMC12047541

What OpenQuestion holds

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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.