ArticleNucleic acids research2014
Discover context-specific combinatorial transcription factor interactions by integrating diverse ChIP-Seq data sets.
Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 22 citations in OpenAlex.
- Article
- Clustering of Sex-Biased Genes and Transposable Elements in the Genome of the Medaka Fish Oryzias latipes.Genome biology and evolution · 2021Article
- Anomaly detection in genomic catalogues using unsupervised multi-view autoencoders.BMC bioinformatics · 2021Article
- Diverse families of transposable elements affect the transcriptional regulation of stress-response genes in Drosophila melanogaster.Nucleic acids research · 2019Article
- Probing transcription factor combinatorics in different promoter classes and in enhancers.BMC genomics · 2019Article
- Novel long-range regulatory mechanisms controlling PKD2 gene expression.BMC genomics · 2018Article
- A graphical model approach visualizes regulatory relationships between genome-wide transcription factor binding profiles.Briefings in bioinformatics · 2018Article
- Transposable Element Exaptation into Regulatory Regions Is Rare, Influenced by Evolutionary Age, and Subject to Pleiotropic Constraints.Molecular biology and evolution · 2017Article
- Regulatory activities of transposable elements: from conflicts to benefits.Nature reviews. Genetics · 2017Review
- Integrative Analysis of Transcription Factor Combinatorial Interactions Using a Bayesian Tensor Factorization Approach.Frontiers in genetics · 2017Article
- Integrative analysis of public ChIP-seq experiments reveals a complex multi-cell regulatory landscape.Nucleic acids research · 2015Article
- Review
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Combinatorial interactions among transcription factors (TFs) are critical for integrating diverse intrinsic and extrinsic signals, fine-tuning regulatory output and increasing the robustness and plasticity of regulatory systems. Current knowledge about combinatorial regulation is rather limited due to the lack of suitable experimental technologies and bioinformatics tools. The rapid accumulation of ChIP-Seq data has provided genome-wide occupancy maps for a large number of TFs and chromatin modification marks for identifying enhancers without knowing individual TF binding sites. Integration of the two data types has not been researched extensively, resulting in underused data and missed opportunities. We describe a novel method for discovering frequent combinatorial occupancy patterns by multiple TFs at enhancers. Our method is based on probabilistic item set mining and takes into account uncertainty in both types of ChIP-Seq data. By joint analysis of 108 TFs in four human cell types, we found that cell-type-specific interactions among TFs are abundant and that the majority of enhancers have flexible architecture. We show that several families of transposable elements disproportionally overlap with enhancers with combinatorial patterns, suggesting that these transposable element families play an important role in the evolution of combinatorial regulation.
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Registered trials
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.