dbCoRC: a database of core transcriptional regulatory circuitries modeled by H3K27ac ChIP-seq signals Article Swipe
Moli Huang
,
Ye Chen
,
Manqiu Yang
,
An‐Yuan Guo
,
Ying Xu
,
Liang Xu
,
H. Phillip Koeffler
·
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.1093/nar/gkx796
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.1093/nar/gkx796
Core transcription regulatory circuitry (CRC) is comprised of a small group of self-regulated transcription factors (TFs) and their interconnected regulatory loops. Studies from embryonic stem cells and other cellular models have revealed the elementary roles of CRCs in transcriptional control of cell identity and cellular fate. Systematic identification and subsequent archiving of CRCs across diverse cell types and tissues are needed to explore both cell/tissue type-specific and disease-associated transcriptional networks. Here, we present a comprehensive and interactive database (dbCoRC, http://dbcorc.cam-su.org) of CRC models which are computationally inferred from mapping of super-enhancer and prediction of TF binding sites. The current version of dbCoRC contains CRC models for 188 human and 50 murine cell lines/tissue samples. In companion with CRC models, this database also provides: (i) super enhancer, typical enhancer, and H3K27ac landscape for individual samples, (ii) putative binding sites of each core TF across the super-enhancer regions within CRC and (iii) expression of each core TF in normal or cancer cells/tissues. The dbCoRC will serve as a valuable resource for the scientific community to explore transcriptional control and regulatory circuitries in biological processes related to, but not limited to lineage specification, tissue homeostasis and tumorigenesis.
Related Topics
Concepts
Enhancer
Biology
Transcription factor
Carcinogenesis
Computational biology
Transcriptional regulation
Regulatory sequence
Cell fate determination
Genetics
Database
Gene
Computer science
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1093/nar/gkx796
- https://academic.oup.com/nar/article-pdf/46/D1/D71/23162540/gkx796.pdf
- OA Status
- gold
- Cited By
- 42
- References
- 46
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2752877137
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2752877137Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1093/nar/gkx796Digital Object Identifier
- Title
-
dbCoRC: a database of core transcriptional regulatory circuitries modeled by H3K27ac ChIP-seq signalsWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2017Year of publication
- Publication date
-
2017-08-30Full publication date if available
- Authors
-
Moli Huang, Ye Chen, Manqiu Yang, An‐Yuan Guo, Ying Xu, Liang Xu, H. Phillip KoefflerList of authors in order
- Landing page
-
https://doi.org/10.1093/nar/gkx796Publisher landing page
- PDF URL
-
https://academic.oup.com/nar/article-pdf/46/D1/D71/23162540/gkx796.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
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https://academic.oup.com/nar/article-pdf/46/D1/D71/23162540/gkx796.pdfDirect OA link when available
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Enhancer, Biology, Transcription factor, Carcinogenesis, Computational biology, Transcriptional regulation, Regulatory sequence, Cell fate determination, Genetics, Database, Gene, Computer scienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
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42Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2024: 3, 2023: 6, 2022: 4, 2021: 11Per-year citation counts (last 5 years)
- References (count)
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46Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.http://dbcorc.cam-su.org) | 79 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 90 |
| corresponding_author_ids | https://openalex.org/A5090664593, https://openalex.org/A5100708993 |
| countries_distinct_count | 3 |
| institutions_distinct_count | 7 |
| corresponding_institution_ids | https://openalex.org/I165932596, https://openalex.org/I3923682, https://openalex.org/I4210103786 |
| citation_normalized_percentile.value | 0.85737778 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |