Evidence map›Paper›PMID 31667506›Full record

ArticleNucleic acids research2020

SEA version 3.0: a comprehensive extension and update of the Super-Enhancer archive.

Chuangeng Chen, Dianshuang Zhou, Yue Gu, Cong Wang, Mengyan Zhang, Xiangyu Lin, Jie Xing, Hongli Wang, Yan Zhang

Abstract read
In one paragraph

Article in Nucleic acids research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers.

0numbers the graph read from it
0cells of the map it votes in
66citing 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

66 citing papers in PubMed.

  1. Article
  2. Review
  3. Crosstalk BetweenCancers · 2026
    Review
  4. ePerturbDB: enhancer's experimental perturbation database.Database : the journal of biological databases and curation · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Transcription Factor-Wide Association Studies to Identify Functional SNPs in Alzheimer's Disease.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
  19. Article
  20. Article

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

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

9 authors.

Chuangeng ChenSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
Dianshuang ZhouSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
Yue GuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Cong WangSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
Mengyan ZhangSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
Xiangyu LinSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
Jie XingSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
Hongli WangSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
Yan ZhangSchool of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Super-enhancers (SEs) are critical for the transcriptional regulation of gene expression. We developed the super-enhancer archive version 3.0 (SEA v. 3.0, http://sea.edbc.org) to extend SE research. SEA v. 3.0 provides the most comprehensive archive to date, consisting of 164 545 super-enhancers. Of these, 80 549 are newly identified from 266 cell types/tissues/diseases using an optimized computational strategy, and 52 have been experimentally confirmed with manually curated references. We now support super-enhancers in 11 species including 7 new species (zebrafish, chicken, chimp, rhesus, sheep, Xenopus tropicalis and stickleback). To facilitate super-enhancer functional analysis, we added several new regulatory datasets including 3 361 785 typical enhancers, chromatin interactions, SNPs, transcription factor binding sites and SpCas9 target sites. We also updated or developed new criteria query, genome visualization and analysis tools for the archive. This includes a tool based on Shannon Entropy to evaluate SE cell type specificity, a new genome browser that enables the visualization of SE spatial interactions based on Hi-C data, and an enhanced enrichment analysis interface that provides online enrichment analyses of SE related genes. SEA v. 3.0 provides a comprehensive database of all available SE information across multiple species, and will facilitate super-enhancer research, especially as related to development and disease.

Indexed as

Databases, Nucleic AcidEnhancer Elements, GeneticAnimalsBinding SitesChromatinHumansPolymorphism, Single NucleotideTranscription FactorsChromatinTranscription Factors

Identifiers

PMID31667506
PMCPMC7145603

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.