The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
AnimalTFDB: a comprehensive animal transcription factor database
Open accessAbstract
Transcription factors (TFs) are proteins that bind to specific DNA sequences, thereby playing crucial roles in gene-expression regulation through controlling the transcription of genetic information from DNA to RNA. Transcription cofactors and chromatin remodeling factors are also essential in the gene transcriptional regulation. Identifying and annotating all the TFs are primary and crucial steps for illustrating their functions and understanding the transcriptional regulation. In this study, based on manual literature reviews, we collected and curated 72 TF families for animals, which is currently the most complete list of TF families in animals. Then, we systematically characterized all the TFs in 50 animal species and constructed a comprehensive animal TF database, AnimalTFDB. To better serve the community, we provided detailed annotations for each TF, including basic information, gene structure, functional domain, 3D structure hit, Gene Ontology, pathway, protein-protein interaction, paralogs, orthologs, potential TF-binding sites and targets. In addition, we collected and annotated transcription cofactors and chromatin remodeling factors. AnimalTFDB has a user-friendly web interface with multiple browse and search functions, as well as data downloading. It is freely available at http://www.bioguo.org/AnimalTFDB/.
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Cites
The Pfam Protein Families Database
Bateman, A. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.1.276 · Cited by 14,000
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Arabidopsis Transcription Factors: Genome-Wide Comparative Analysis Among Eukaryotes
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The Pfam protein families database
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TRANSFAC(R) and its module TRANSCompel(R): transcriptional gene regulation in eukaryotes
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JASPAR 2010: the greatly expanded open-access database of transcription factor binding profiles
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Cited by
Zhang, Y., Chen, K., Sloan, S. A., Bennett, M. L., Scholze, A. R., O'Keeffe, S., Phatnani, H. P., Guarnieri, P., Caneda, C., Ruderisch, N., et al. (2014) · The Journal of Neuroscience · doi:10.1523/jneurosci.1860-14.2014 · Cited by 4,875
“To identify cell type-enriched transcription factors, we filtered our data with a previously annotated transcription factor database (Zhang et al., 2012), and top enriched transcription factors of each cell type were identified as described above.”
MethodSuper-enhancers in the control of cell identity and disease
Hnisz, D., Abraham, B. J., Lee, T. I., Lau, A., Saint-André, V., Sigova, A. A., Hoke, H. A., & Young, R. A. (2013) · Cell · doi:10.1016/j.cell.2013.09.053 · Cited by 3,662
Recovering Gene Interactions from Single-Cell Data Using Data Diffusion
van Dijk, D., Sharma, R., Nainys, J., Yim, K., Kathail, P., Carr, A. J., Burdziak, C., Moon, K. R., Chaffer, C. L., Pattabiraman, D., et al. (2018) · Cell · doi:10.1016/j.cell.2018.05.061 · Cited by 1,829
A single-cell survey of the small intestinal epithelium
Haber, A. L., Biton, M., Rogel, N., Herbst, R. H., Shekhar, K., Smillie, C., Burgin, G., Delorey, T. M., Howitt, M. R., Katz, Y., et al. (2017) · Nature · doi:10.1038/nature24489 · Cited by 1,750
Reconstructing lineage hierarchies of the distal lung epithelium using single-cell RNA-seq
Treutlein, B., Brownfield, D. G., Wu, A. R., Neff, N. F., Mantalas, G. L., Espinoza, F. H., Desai, T. J., Krasnow, M. A., & Quake, S. R. (2014) · Nature · doi:10.1038/nature13173 · Cited by 1,342
Metadata
- Authors
- Zhang, H.-M., Chen, H., Liu, W., Liu, H., Gong, J., Wang, H., & Guo, A.-Y.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-11-12
- Volume
- 40
- Issue
- D1
- Pages
- D144-D149
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W2075406901
- Cited by
- 300
- References
- 24
- FWCI
- 4.47
- Type
- journal article
- Language
- en
- Open access
- gold
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- Zhang, H.-M., Chen, H., Liu, W., Liu, H., Gong, J., Wang, H., & Guo, A.-Y. (2012). AnimalTFDB: a comprehensive animal transcription factor database. Nucleic Acids Research. https://doi.org/10.1093/nar/gkr965
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
