ArticleComputational and structural biotechnology journal2024
TFTG: A comprehensive database for human transcription factors and their targets.
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.
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Who cites it
5 citing papers in PubMed.
- Intratumoral Microbiota Correlates with AP-2 Expression: A Pan-Cancer Map with Cohort-Specific Prognostic and Molecular Footprints.International journal of molecular sciences · 2025Article
- MatriCom, a single-cell RNA-sequencing data mining tool to infer cell-extracellular matrix interactions.Journal of cell science · 2025Article
- TRAPT: a multi-stage fused deep learning framework for predicting transcriptional regulators based on large-scale epigenomic data.Nature communications · 2025Article
- Transcriptional coordination between intergenic RNA polymerase II-bound regions and nearby genes reveals functional specialization and disease associations in peripheral blood.Computational and structural biotechnology journal · 2025Article
- An Integrated Strategy for Analyzing the Complete Complex Integrated Structure of Maize MON810 and Identification of an SNP in External Insertion Sequences.Plants (Basel, Switzerland) · 2024Article
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16 authors.
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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.
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