Evidence map›Paper›PMID 41606153›Full record

ArticleNature2026

Advancing regulatory variant effect prediction with AlphaGenome.

Žiga Avsec, Natasha Latysheva, Jun Cheng, Guido Novati, Kyle R Taylor, Tom Ward, Clare Bycroft, Lauren Nicolaisen, Eirini Arvaniti, Joshua Pan and 17 more

Abstract read
In one paragraph

Article in Nature, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 180 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
180citing papers in PubMed, 3 pooled it
–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

180 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Review
  13. AlphaGenome Atlas:medRxiv : the preprint server for health sciences · 2026
    Article
  14. Article
  15. Machine learning reveals sequence and genomic context features underlyingbioRxiv : the preprint server for biology · 2026
    Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Article

120 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

27 authors.

Žiga Avsec *Google DeepMind, London, UK. avsec@google.com.ORCID 0000-0003-3119-0567
Natasha Latysheva *Google DeepMind, London, UK.
Jun Cheng *Google DeepMind, London, UK.
Guido Novati *Google DeepMind, London, UK.ORCID 0000-0003-0681-4892
Kyle R Taylor *Google DeepMind, London, UK.
Tom Ward *Google DeepMind, London, UK.
Clare Bycroft *Google DeepMind, London, UK.ORCID 0000-0002-1139-0732
Lauren Nicolaisen *Google DeepMind, London, UK.
Eirini Arvaniti *Google DeepMind, London, UK.
Joshua Pan *Google DeepMind, London, UK.
Raina ThomasGoogle DeepMind, London, UK.ORCID 0000-0001-8027-3460
Vincent DutordoirGoogle DeepMind, London, UK.
Matteo PerinoGoogle DeepMind, London, UK.
Soham DeGoogle DeepMind, London, UK.
Alexander KarollusGoogle DeepMind, London, UK.
Adam GayosoGoogle DeepMind, London, UK.
Toby SargeantGoogle DeepMind, London, UK.
Anne MottramGoogle DeepMind, London, UK.
Lai Hong WongGoogle DeepMind, London, UK.
Pavol DrotárGoogle DeepMind, London, UK.
Adam KosiorekGoogle DeepMind, London, UK.
Andrew SeniorGoogle DeepMind, London, UK.ORCID 0000-0002-2401-5691
Richard TanburnGoogle DeepMind, London, UK.
Taylor ApplebaumGoogle DeepMind, London, UK.
Souradeep BasuGoogle DeepMind, London, UK.
Demis HassabisGoogle DeepMind, London, UK.
Pushmeet KohliGoogle DeepMind, London, UK. pushmeet@google.com.ORCID 0000-0002-7466-7997

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deep learning models that predict functional genomic measurements from DNA sequences are powerful tools for deciphering the genetic regulatory code. Existing methods involve a trade-off between input sequence length and prediction resolution, thereby limiting their modality scope and performance

Indexed as

Deep LearningGenetic VariationGenomeGenome, HumanSequence Analysis, DNAAnimalsChromatinGene Expression RegulationGenomicsHumansMiceModels, GeneticProto-Oncogene ProteinsRNA Splice SitesTranscription FactorsChromatinProto-Oncogene ProteinsRNA Splice SitesTranscription Factors

Identifiers

PMID41606153
PMCPMC12851941

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.