Evidence map›Paper›PMID 38707542›Full record

ArticleComputational and structural biotechnology journal2024

TFTG: A comprehensive database for human transcription factors and their targets.

Xinyuan Zhou, Liwei Zhou, Fengcui Qian, Jiaxin Chen, Yuexin Zhang, Zhengmin Yu, Jian Zhang, Yongsan Yang, Yanyu Li, Chao Song and 6 more

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Xinyuan ZhouThe First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China.
Liwei ZhouState Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
Fengcui QianThe First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China.
Jiaxin ChenSchool of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China.
Yuexin ZhangThe First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China.
Zhengmin YuSchool of Computer, University of South China, Hengyang, Hunan 421001, China.
Jian ZhangSchool of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China.
Yongsan YangSchool of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China.
Yanyu LiSchool of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China.
Chao SongThe First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China.
Yuezhu WangSchool of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China.
Desi ShangThe First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China.
Longlong DongSchool of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China.
Jiang ZhuSchool of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China.
Chunquan LiThe First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China.
Qiuyu WangThe First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transcription factors (TFs) are major contributors to gene transcription, especially in controlling cell-specific gene expression and disease occurrence and development. Uncovering the relationship between TFs and their target genes is critical to understanding the mechanism of action of TFs. With the development of high-throughput sequencing techniques, a large amount of TF-related data has accumulated, which can be used to identify their target genes. In this study, we developed TFTG (Transcription Factor and Target Genes) database (http://tf.liclab.net/TFTG), which aimed to provide a large number of available human TF-target gene resources by multiple strategies, besides performing a comprehensive functional and epigenetic annotations and regulatory analyses of TFs. We identified extensive available TF-target genes by collecting and processing TF-associated ChIP-seq datasets, perturbation RNA-seq datasets and motifs. We also obtained experimentally confirmed relationships between TF and target genes from available resources. Overall, the target genes of TFs were obtained through integrating the relevant data of various TFs as well as fourteen identification strategies. Meanwhile, TFTG was embedded with user-friendly search, analysis, browsing, downloading and visualization functions. TFTG is designed to be a convenient resource for exploring human TF-target gene regulations, which will be useful for most users in the TF and gene expression regulation research.

Indexed as

Enrichment analysisEpigenetic annotationFunctional annotationTarget geneTranscription factor

Identifiers

PMID38707542
PMCPMC11068477

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.