Evidence mapPaperPMID 41171129Full record

ArticleNucleic acids research2026

SEA version 4.0: a major expansion and update of the Super-Enhancer Archive.

Bowen Shi, Jiyun Zhao, Yu Li, Chenye Zhang, Longhao Deng, Chengzhi Ji, Hongli Wang, Ruiyang Zhai, Tao Feng, Yan Zhang and 1 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Bowen ShiSchool of Life Science and Technology, Faculty of Life Sciences and Medicine, Harbin Institute of Technology, Harbin 150001, China.
Jiyun ZhaoSchool of Life Science and Technology, Faculty of Life Sciences and Medicine, Harbin Institute of Technology, Harbin 150001, China.
Yu LiCollege of Pathology, Qiqihar Medical University, Qiqihar 161042, China.
Chenye ZhangSchool of Life Science and Technology, Faculty of Life Sciences and Medicine, Harbin Institute of Technology, Harbin 150001, China.
Longhao DengSchool of Life Science and Technology, Faculty of Life Sciences and Medicine, Harbin Institute of Technology, Harbin 150001, China.
Chengzhi JiSchool of Life Science and Technology, Faculty of Life Sciences and Medicine, Harbin Institute of Technology, Harbin 150001, China.
Hongli WangSchool of Life Science and Technology, Faculty of Life Sciences and Medicine, Harbin Institute of Technology, Harbin 150001, China.
Ruiyang ZhaiSchool of Life Science and Technology, Faculty of Life Sciences and Medicine, Harbin Institute of Technology, Harbin 150001, China.
Tao FengThe Fourth Hospital of Harbin Medical University, Harbin 150080, China.
Yan ZhangCollege of Pathology, Qiqihar Medical University, Qiqihar 161042, China.ORCID 0000-0002-5307-2484
Yue GuSchool of Life Science and Technology, Faculty of Life Sciences and Medicine, Harbin Institute of Technology, Harbin 150001, China.

Funding

Fundamental Research Funds for the Central Universities LH2024F020National Natural Science Foundation of China 62372141Qiqihar City Joint Guidance Project of Science and Technology Program LSFGG-2024101
6 · The paper itself

Abstract

Super-enhancers (SEs) are pivotal epigenetic regulatory elements that profoundly influence cell fate and disease. We herein present an updated SEA version 4.0, a systematic platform designed to elucidate the roles of SEs. A uniform computational pipeline was established to identify SEs based on five key histone marks, using H3K27ac, BRD4, p300, Med1, and the newly added H3K4me1, across 14 species. 496 071 SEs and 29 584 078 enhancers have been stored in the database. It provides extensive genome annotations, including nearby genes, transcription factor binding sites, chromatin accessibility, and other gene regulation signatures. SEA version 4.0 has also achieved functional enrichment analysis of SEs. And a Shannon entropy-based algorithm is employed to identify specific SEs. Furthermore, SEA version 4.0 introduces an interactive regulatory network that incorporates SEs, enhancers, transcription factors, and proximal genes for human and mouse. Additionally, a cell-specific SE detector is provided, designed for cancer research by leveraging scRNA-seq data from 12 cancer and normal samples to explore cell-type-specific SEs. The performance interaction and visualization of SEA version 4.0 enable genomic and cross-species comparisons, revealing complex genomic interactions and becoming an indispensable resource for decoding the mechanisms of SE in development and disease. Access freely at http://sea4.edbc.org.

Indexed as

Databases, GeneticEnhancer Elements, GeneticSoftwareAlgorithmsAnimalsBinding SitesChromatinComputational BiologyGene Regulatory NetworksHistone CodeHistonesHumansMiceMolecular Sequence AnnotationNeoplasmsTranscription FactorsChromatinHistonesTranscription Factors

Identifiers

PMID41171129
PMCPMC12807652

What Socratic holds

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LicenceCC BY
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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.