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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LINGER outperforms all other methods in predicting direct differentially expressed genes under TF perturbation using eight PBMC datasets from KnockTF (P ≤ 3.72 × 10−4).
“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]
The Introduction identifies KnockTF as a database of human TF knockdown/knockout expression datasets, and Data Source and Processing describes its differentially expressed gene analyses. This supports citing KnockTF as a data source, but our copy does not report eight PBMC datasets or compare LINGER with other methods; it does not support the stated performance result or P-value. (LLM, conf=0.86)
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- 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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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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