Database Commons
Database Commons

a catalog of worldwide biological databases

Database Profile

SEA

General information

URL: http://sea.edbc.org
Full name: Super-Enhancer Archive
Description: Super-Enhancer Archive is a web based comprehensive resource focuses on the collection, storage and online analysis of super-enhancers. Our mission is to provide a curated set of information datasets for super-enhancers and tools in mutiple genomes, to support and promote research in this area. Especially, we provide a genome-scale landscape to show super-enhancer information in a scalable and flexible manner.
Year founded: 2016
Last update: 2015-10-25
Version: v1.0
Accessibility:
Accessible
Country/Region: China

Classification & Tag

Data type:
DNA
Data object:
Database category:
Major species:
Keywords:

Contact information

University/Institution: Harbin Institute of Technology
Address: School of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China
City: Harbin
Province/State: Heilongjiang
Country/Region: China
Contact name (PI/Team): Yan Zhang
Contact email (PI/Helpdesk): zhangtyo@hit.edu.cn

Publications

31667506
SEA version 3.0: a comprehensive extension and update of the Super-Enhancer archive. [PMID: 31667506]
Chen C, Zhou D, Gu Y, Wang C, Zhang M, Lin X, Xing J, Wang H, Zhang Y.

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.

Nucleic Acids Res. 2020:48(D1) | 64 Citations (from Europe PMC, 2025-12-13)
26578594
SEA: a super-enhancer archive. [PMID: 26578594]
Wei Y, Zhang S, Shang S, Zhang B, Li S, Wang X, Wang F, Su J, Wu Q, Liu H, Zhang Y.

Super-enhancers are large clusters of transcriptional enhancers regarded as having essential roles in driving the expression of genes that control cell identity during development and tumorigenesis. The construction of a genome-wide super-enhancer database is urgently needed to better understand super-enhancer-directed gene expression regulation for a given biology process. Here, we present a specifically designed web-accessible database, Super-Enhancer Archive (SEA, http://sea.edbc.org). SEA focuses on integrating super-enhancers in multiple species and annotating their potential roles in the regulation of cell identity gene expression. The current release of SEA incorporates 83 996 super-enhancers computationally or experimentally identified in 134 cell types/tissues/diseases, including human (75 439, three of which were experimentally identified), mouse (5879, five of which were experimentally identified), Drosophila melanogaster (1774) and Caenorhabditis elegans (904). To facilitate data extraction, SEA supports multiple search options, including species, genome location, gene name, cell type/tissue and super-enhancer name. The response provides detailed (epi)genetic information, incorporating cell type specificity, nearby genes, transcriptional factor binding sites, CRISPR/Cas9 target sites, evolutionary conservation, SNPs, H3K27ac, DNA methylation, gene expression and TF ChIP-seq data. Moreover, analytical tools and a genome browser were developed for users to explore super-enhancers and their roles in defining cell identity and disease processes in depth. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Nucleic Acids Res. 2016:44(D1) | 80 Citations (from Europe PMC, 2025-12-13)

Ranking

All databases:
1007/6895 (85.41%)
Expression:
190/1347 (85.969%)
Modification:
59/337 (82.789%)
1007
Total Rank
133
Citations
14.778
z-index

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Record metadata

Created on: 2016-01-06
Curated by:
Pei Liu [2022-08-31]
Chang Liu [2020-11-07]
Lin Xia [2016-03-29]
Lin Liu [2016-02-08]
Lin Liu [2016-01-27]
Lin Liu [2016-01-06]