ArticleGenome research2019
Leveraging chromatin accessibility for transcriptional regulatory network inference in T Helper 17 Cells.
Article in Genome research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers.
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Who cites it
65 citing papers in PubMed, 113 citations in OpenAlex.
- Epistatic chromatin remodeling during barley response to powdery mildew by ATAC-Seq.Scientific data · 2026Article
- Gene regulatory network determinants of rapid recall in human memory CD4Cell reports · 2026Article
- A network-based model of Aspergillus fumigatus elucidates regulators of development and defensive natural products of an opportunistic pathogen.Nucleic acids research · 2026Article
- Genome-wide nucleosome and transcription factor responses to genetic perturbations reveal chromatin-mediated mechanisms of transcriptional regulation.Genome research · 2026Article
- Bile acids engage the SIPR-STAT3 signaling axis to modulate regulatory T cell responses in fibrosing cholangiopathies.Journal of hepatology · 2025Article
- A multimodal cross-species comparison of pancreas development.Nature communications · 2025Article
- An efficient framework to decipher microRNA regulatory programs applied to T cells.Genes and immunity · 2025Article
- Leveraging transcription factor physical proximity for enhancing gene regulation inference.Bioinformatics (Oxford, England) · 2025Article
- Perspective on recent developments and challenges in regulatory and systems genomics.Bioinformatics advances · 2025Review
- T-follicular helper cells are epigenetically poised to transdifferentiate into T-regulatory type 1 cells.eLife · 2024Article
- Optimizing data integration improves gene regulatory network inference in Arabidopsis thaliana.Bioinformatics (Oxford, England) · 2024Article
- A genome scale transcriptional regulatory model of the human placenta.Science advances · 2024Article
- Functional CRISPR screens in T cells reveal new opportunities for cancer immunotherapies.Molecular cancer · 2024Review
- Integrated characterization of hepatobiliary tumor organoids provides a potential landscape of pharmacogenomic interactions.Cell reports. Medicine · 2024Article
- Splicing neoantigen discovery with SNAF reveals shared targets for cancer immunotherapy.Science translational medicine · 2024Article
- Current and future directions in network biology.Bioinformatics advances · 2024Article
- Decoding mutational hotspots in human disease through the gene modules governing thymic regulatory T cells.Frontiers in immunology · 2024Article
- Inferring Dynamic Regulatory Interaction Graphs from Time Series Data with Perturbations.Proceedings of machine learning research · 2024Article
- Stem cell-like reprogramming is required for leukemia-initiating activity in B-ALL.The Journal of experimental medicine · 2024Article
- Alveolar epithelial progenitor cells require Nkx2-1 to maintain progenitor-specific epigenomic state during lung homeostasis and regeneration.Nature communications · 2023Article
5 more citing papers are in PubMed but not listed here.
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Authors and funding
12 authors at 6 institutions in 1 country.
Funding
Abstract
Transcriptional regulatory networks (TRNs) provide insight into cellular behavior by describing interactions between transcription factors (TFs) and their gene targets. The assay for transposase-accessible chromatin (ATAC)-seq, coupled with TF motif analysis, provides indirect evidence of chromatin binding for hundreds of TFs genome-wide. Here, we propose methods for TRN inference in a mammalian setting, using ATAC-seq data to improve gene expression modeling. We test our methods in the context of T Helper Cell Type 17 (Th17) differentiation, generating new ATAC-seq data to complement existing Th17 genomic resources. In this resource-rich mammalian setting, our extensive benchmarking provides quantitative, genome-scale evaluation of TRN inference, combining ATAC-seq and RNA-seq data. We refine and extend our previous Th17 TRN, using our new TRN inference methods to integrate all Th17 data (gene expression, ATAC-seq, TF knockouts, and ChIP-seq). We highlight newly discovered roles for individual TFs and groups of TFs ("TF-TF modules") in Th17 gene regulation. Given the popularity of ATAC-seq, which provides high-resolution with low sample input requirements, we anticipate that our methods will improve TRN inference in new mammalian systems, especially in vivo, for cells directly from humans and animal models.
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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.