Evidence map›Paper›PMID 33603233›Full record

ArticleNature genetics2021

Base-resolution models of transcription-factor binding reveal soft motif syntax.

Žiga Avsec, Melanie Weilert, Avanti Shrikumar, Sabrina Krueger, Amr Alexandari, Khyati Dalal, Robin Fropf, Charles McAnany, Julien Gagneur, Anshul Kundaje and 1 more

Abstract read
In one paragraph

Article in Nature genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 403 papers.

0numbers the graph read from it
0cells of the map it votes in
403citing 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

403 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. AlphaGenome Atlas:medRxiv : the preprint server for health sciences · 2026
    Article
  6. Article
  7. Article
  8. Article
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  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. The Encyclopedia of DNA Elements.bioRxiv : the preprint server for biology · 2026
    Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Evolution of CTCF binding sites in the human genome.Molecular biology and evolution · 2026
    Article

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

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Žiga AvsecDepartment of Informatics, Technical University of Munich, Garching, Germany.ORCID http://orcid.org/0000-0002-7790-8936
Melanie WeilertStowers Institute for Medical Research, Kansas City, MO, USA.
Avanti ShrikumarDepartment of Computer Science, Stanford University, Stanford, CA, USA.
Sabrina KruegerStowers Institute for Medical Research, Kansas City, MO, USA.
Amr AlexandariDepartment of Computer Science, Stanford University, Stanford, CA, USA.
Khyati DalalStowers Institute for Medical Research, Kansas City, MO, USA.
Robin FropfStowers Institute for Medical Research, Kansas City, MO, USA.
Charles McAnanyStowers Institute for Medical Research, Kansas City, MO, USA.
Julien GagneurDepartment of Informatics, Technical University of Munich, Garching, Germany.ORCID http://orcid.org/0000-0002-8924-8365
Anshul KundajeDepartment of Computer Science, Stanford University, Stanford, CA, USA. akundaje@stanford.edu.ORCID http://orcid.org/0000-0003-3084-2287
Julia ZeitlingerStowers Institute for Medical Research, Kansas City, MO, USA. jbz@stowers.org.

Funding

Using PCORnet to Expand the DS-CONNECT Cohort Through Healthcare System Recruitment, Incorporating Electronic Health Records, and Assessing Self-DeterminationU54HD090216 · NICHD · UNIVERSITY OF KANSAS LAWRENCE · PI MC CARSON, KENNETH E · 2016 to 2020
$6.2M
Molecular Regulation of Cell Development and Differentiation Phase III COBREP30GM122731 · NIGMS · UNIVERSITY OF KANSAS MEDICAL CENTER · PI ABRAHAMSON, DALE R · 2017 to 2021
$5.6M
Decoding the regulatory architecture of the human genome across cell types, individuals and diseaseU01HG009431 · NHGRI · STANFORD UNIVERSITY · PI PRITCHARD, JONATHAN K · 2017 to 2021
$3.5M
Deep learning frameworks for regulatory genomics.DP2GM123485 · NIGMS · STANFORD UNIVERSITY · PI KUNDAJE, ANSHUL · 2016 to 2016
$2.4M
A transposase system for integrative ChIP-exo and ATAC-seq analysis at single-cell resolutionR01HG010211 · NHGRI · STOWERS INSTITUTE FOR MEDICAL RESEARCH · PI ZEITLINGER, JULIA · 2018 to 2021
$2.3M
Learning Regulatory Drivers of Chromatin and Expression Dynamics during Nuclear ReprogrammingR01HG009674 · NHGRI · STANFORD UNIVERSITY · PI BLAU, HELEN M, KUNDAJE, ANSHUL · 2017 to 2019
$2.1M
High Throughput Sequencing System for KUMC Genomics CoreS10OD021743 · OD · UNIVERSITY OF KANSAS MEDICAL CENTER · PI SMITH, PETER G · 2017 to 2017
$493k
Howard Hughes Medical InstituteNHGRI NIH HHS R01 HG009674NHGRI NIH HHS R01 HG010211NHGRI NIH HHS U01 HG009431NICHD NIH HHS U54 HD090216NIGMS NIH HHS DP2 GM123485NIGMS NIH HHS P30 GM122731NIH HHS S10 OD021743
6 · The paper itself

Abstract

The arrangement (syntax) of transcription factor (TF) binding motifs is an important part of the cis-regulatory code, yet remains elusive. We introduce a deep learning model, BPNet, that uses DNA sequence to predict base-resolution chromatin immunoprecipitation (ChIP)-nexus binding profiles of pluripotency TFs. We develop interpretation tools to learn predictive motif representations and identify soft syntax rules for cooperative TF binding interactions. Strikingly, Nanog preferentially binds with helical periodicity, and TFs often cooperate in a directional manner, which we validate using clustered regularly interspaced short palindromic repeat (CRISPR)-induced point mutations. Our model represents a powerful general approach to uncover the motifs and syntax of cis-regulatory sequences in genomics data.

Indexed as

Nucleotide MotifsAnimalsBinding SitesChromatin ImmunoprecipitationClustered Regularly Interspaced Short Palindromic RepeatsComputational BiologyDeep LearningMiceMouse Embryonic Stem CellsNanog Homeobox ProteinNeural Networks, ComputerOctamer Transcription Factor-3Reproducibility of ResultsSOXB1 Transcription FactorsTranscription FactorsNanog Homeobox ProteinNanog protein, mouseOctamer Transcription Factor-3Pou5f1 protein, mouseSox2 protein, mouseSOXB1 Transcription FactorsTranscription Factors

Identifiers

PMID33603233
PMCPMC8812996

What Socratic holds

Textmetadata
LicenceTDM
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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 Socratic graph.