ArticleNucleic acids research2014
Systematic discovery and characterization of regulatory motifs in ENCODE TF binding experiments.
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 282 papers, 6 of them syntheses that pooled it.
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Who cites it
282 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- Association between an AMH promoter polymorphism and serum AMH levels in PCOS patients.Human reproduction (Oxford, England) · 2022Pooled it
- Genome-wide meta-analysis of monoclonal gammopathy of undetermined significance (MGUS) identifies risk loci impacting IRF-6.Blood cancer journal · 2022Pooled it
- Leverage Large-Scale Biological Networks to Decipher the Genetic Basis of Human Diseases Using Machine Learning.Methods in molecular biology (Clifton, N.J.) · 2021Pooled it
- Genome-wide meta-analysis identifies eight new susceptibility loci for cutaneous squamous cell carcinoma.Nature communications · 2020Pooled it
- Meta-analysis of massively parallel reporter assays enables prediction of regulatory function across cell types.Human mutation · 2019Pooled it
- Genome-Wide Interactions with Dairy Intake for Body Mass Index in Adults of European Descent.Molecular nutrition & food research · 2018Pooled it
- Polymorphism in interferon alpha/beta receptor contributes to glucocorticoid response and outcome of ARDS and COVID-19.Critical care (London, England) · 2023Trial
- Sugar-Sweetened Beverage Consumption May Modify Associations Between Genetic Variants in the CHREBP (Carbohydrate Responsive Element Binding Protein) Locus and HDL-C (High-Density Lipoprotein Cholesterol) and Triglyceride Concentrations.Circulation. Genomic and precision medicine · 2021Trial
- Tissue-resident immune cells drive genetic risk in autoimmune and lung diseases.Nature immunology · 2026Article
- FUS controls muscle differentiation through phase separation-mediated recruitment of the transcription factors MEF2 and ETV5.The EMBO journal · 2026Article
- Comparing machine learning methods predicting transcriptome from epigenome with applications to association studies.Genome biology · 2026Article
- Functional motif detection via in silico ablation using AlphaGenome.Briefings in bioinformatics · 2026Article
- Integrative Mapping of Regulatory Variation in African American Hepatocytes Using Colocalization and MPRA: Toward Precision Drug Response.Research square · 2026Article
- Probing transcription factor subsets in gene regulatory networks.Algorithms for molecular biology : AMB · 2026Article
- Article
- Cell type-specific epigenetic regulatory circuitry of coronary artery disease loci.Nature communications · 2026Article
- Liver single-nucleus multiome profiling reveals cell-type mechanisms for cardiometabolic traits.American journal of human genetics · 2026Article
- Exploring potential transcription factors and their regulatory relationships based on asymmetric covariance natural vector encoding method and machine learning algorithms.Briefings in bioinformatics · 2026Article
- MotifPeeker: benchmarking epigenomic profiling methods using motifs.Bioinformatics advances · 2026Article
- LIPA, a risk locus for coronary artery disease: decoding the variant-to-function relationship.European heart journal · 2025Article
222 more citing papers are in PubMed but not listed here.
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2 authors.
Funding
Abstract
Recent advances in technology have led to a dramatic increase in the number of available transcription factor ChIP-seq and ChIP-chip data sets. Understanding the motif content of these data sets is an important step in understanding the underlying mechanisms of regulation. Here we provide a systematic motif analysis for 427 human ChIP-seq data sets using motifs curated from the literature and also discovered de novo using five established motif discovery tools. We use a systematic pipeline for calculating motif enrichment in each data set, providing a principled way for choosing between motif variants found in the literature and for flagging potentially problematic data sets. Our analysis confirms the known specificity of 41 of the 56 analyzed factor groups and reveals motifs of potential cofactors. We also use cell type-specific binding to find factors active in specific conditions. The resource we provide is accessible both for browsing a small number of factors and for performing large-scale systematic analyses. We provide motif matrices, instances and enrichments in each of the ENCODE data sets. The motifs discovered here have been used in parallel studies to validate the specificity of antibodies, understand cooperativity between data sets and measure the variation of motif binding across individuals and species.
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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 Socratic graph.