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KnockTF: a comprehensive human gene expression profile database with knockdown/knockout of transcription factors
Open accessAbstract
Transcription factors (TFs) and their target genes have important functions in human diseases and biological processes. Gene expression profile analysis before and after knockdown or knockout is one of the most important strategies for obtaining target genes of TFs and exploring TF functions. Human gene expression profile datasets with TF knockdown and knockout are accumulating rapidly. Based on the urgent need to comprehensively and effectively collect and process these data, we developed KnockTF (http://www.licpathway.net/KnockTF/index.html), a comprehensive human gene expression profile database of TF knockdown and knockout. KnockTF provides a number of resources for human gene expression profile datasets associated with TF knockdown and knockout and annotates TFs and their target genes in a tissue/cell type-specific manner. The current version of KnockTF has 570 manually curated RNA-seq and microarray datasets associated with 308 TFs disrupted by different knockdown and knockout techniques and across multiple tissue/cell types. KnockTF collects upstream pathway information of TFs and functional annotation results of downstream target genes. It provides details about TFs binding to promoters, super-enhancers and typical enhancers of target genes. KnockTF constructs a TF-differentially expressed gene network and performs network analyses for genes of interest. KnockTF will help elucidate TF-related functions and potential biological effects.
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“Extended Data Fig. 4a,b shows that LINGER outperforms all other methods (P ≤ 3.72 × 10−4).”
From Inferring gene regulatory networks from single-cell multiome data using atlas-scale external data (2025) · cites this paper as [59]
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Cites
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
limma powers differential expression analyses for RNA-sequencing and microarray studies
Ritchie, M. E., Phipson, B., Wu, D., Hu, Y., Law, C. W., Shi, W., & Smyth, G. K. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv007 · Cited by 40,458
BEDTools: a flexible suite of utilities for comparing genomic features
Quinlan, A. R., & Hall, I. M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq033 · Cited by 27,437
Multiplex Genome Engineering Using CRISPR/Cas Systems
Cong, L., Ran, F. A., Cox, D., Lin, S., Barretto, R., Habib, N., Hsu, P. D., Wu, X., Jiang, W., Marraffini, L. A., et al. (2013) · Science · doi:10.1126/science.1231143 · Cited by 15,339
NCBI GEO: archive for functional genomics data sets—update
Barrett, T., Wilhite, S. E., Ledoux, P., Evangelista, C., Kim, I. F., Tomashevsky, M., Marshall, K. A., Phillippy, K. H., Sherman, P. M., Holko, M., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1193 · Cited by 10,418
Duplexes of 21-nucleotide RNAs mediate RNA interference in cultured mammalian cells
Elbashir, S. M., Harborth, J., Lendeckel, W., Yalcin, A., Weber, K., & Tuschl, T. (2001) · Nature · doi:10.1038/35078107 · Cited by 9,456
KEGG: new perspectives on genomes, pathways, diseases and drugs
Kanehisa, M., Furumichi, M., Tanabe, M., Sato, Y., & Morishima, K. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw1092 · Cited by 8,865
The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity
Barretina, J., Caponigro, G., Stransky, N., Venkatesan, K., Margolin, A. A., Kim, S., Wilson, C. J., Lehár, J., Kryukov, G. V., Sonkin, D., et al. (2012) · Nature · doi:10.1038/nature11003 · Cited by 7,950
Bailey, T. L., Johnson, J., Grant, C. E., & Noble, W. S. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv416 · Cited by 5,442
Programmable editing of a target base in genomic DNA without double-stranded DNA cleavage
Komor, A. C., Kim, Y. B., Packer, M. S., Zuris, J. A., & Liu, D. R. (2016) · Nature · doi:10.1038/nature17946 · Cited by 5,437
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Metadata
- Authors
- Feng, C., Song, C., Liu, Y., Qian, F., Gao, Y., Ning, Z., Wang, Q., Jiang, Y., Li, Y., Li, M., Chen, J., Zhang, J., & Li, C.
- Affiliations
- Harbin Medical University (CN)
- Corresponding author
- Zhang, Jian
- Li, Chunquan
- ORCID
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2019-10-10
- Volume
- 48
- Issue
- D1
- Pages
- D93-D100
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC6943067
- OpenAlex
- W2979799397
- Cited by
- 147
- References
- 48
- Citations by year
- 2026: 17 · 2025: 26 · 2024: 29 · 2023: 27 · 2022: 15 · 2021: 25 · 2020: 7 · 2019: 1
- FWCI
- 3.97
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Nucleic Acids Research (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (81572341, 61601150)
- National Science Foundation (YQ2019C013)
- Yu Weihan Outstanding Youth Training Fund of Harbin Medical University
- Wu Liande Youth Science Research Fund of Harbin Medical University (DQWLD201703)
- Scientific Research Fund of Harbin Medical University (DQXN201707)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Keywords
- transcription factors, transcription factor target genes, gene expression profiling, knockdown, knockout, RNA-seq, microarray, tissue-specific gene expression, super-enhancers, enhancers, promoter binding, functional annotation
- MeSH terms
- Humans, Software, Transcription Factors, User-Computer Interface, Computational Biology, Gene Expression Profiling, Databases, Genetic, Gene Knockdown Techniques, Molecular Sequence Annotation, Web Browser
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