ArticleNature methods2020
Supervised enhancer prediction with epigenetic pattern recognition and targeted validation.
Article in Nature methods, 2020. 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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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.
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Who cites it
65 citing papers in PubMed.
- Hybrid CNN and multi-head attention model for analyzing epigenetic mechanisms and gene expression across fungal phylogenetic distances.iScience · 2026Article
- Predictive design of tissue-specific mammalian enhancers that function in the mouse embryo.Nature genetics · 2026Article
- Integrating dietary patterns and metabolomics with machine learning for metabolic syndrome risk assessment in a rural population.NPJ science of food · 2026Article
- Article
- Transcriptional competence defines the heterochromatin nucleating potential of isolated MSR units.Nature communications · 2026Article
- Functional interrogation of candidate cis-regulatory elements at the LDLR locus.PLoS genetics · 2026Article
- Extrusion fountains are hallmarks of chromosome organization emerging upon zygotic genome activation.Nature communications · 2026Article
- TGFβ signaling promotes cell cycle progression and resistance to the CDK4/6 inhibitor palbociclib through SOX4 transcriptional modulation in breast cancer cells.Cell death & disease · 2026Article
- mwHIT: accelerated and accurate histone modification imputation using multi-scale window attention.Frontiers in genetics · 2026Article
- Functional maps of a genomic locus reveal confinement of an enhancer by its target gene.Science (New York, N.Y.) · 2025Article
- A map of enhancer regions in primary human neural progenitor cells using capture STARR-seq.Genome research · 2025Article
- Extrusion fountains are hallmarks of chromosome organization emerging upon zygotic genome activation.bioRxiv : the preprint server for biology · 2025Article
- DEK-nucleosome structure shows DEK modulates H3K27me3 and stem cell fate.Nature structural & molecular biology · 2025Article
- YAP controls cell migration and invasion through a Rho GTPase switch.Science signaling · 2025Article
- ChromActivity: integrative epigenomic and functional characterization assay based annotation of regulatory activity across diverse human cell types.Genome biology · 2025Article
- Prediction of gene expression using histone modification patterns extracted by Particle Swarm Optimization.Bioinformatics (Oxford, England) · 2025Article
- Functional Validation of Noncoding Variants Associated With Nonsyndromic Orofacial Cleft.Human mutation · 2025Review
- Functional characteristics and computational model of abundant hyperactive loci in the human genome.eLife · 2024Article
- Review and Evaluate the Bioinformatics Analysis Strategies of ATAC-seq and CUT&Tag Data.Genomics, proteomics & bioinformatics · 2024Review
- Review
5 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
25 authors.
Funding
Abstract
Enhancers are important non-coding elements, but they have traditionally been hard to characterize experimentally. The development of massively parallel assays allows the characterization of large numbers of enhancers for the first time. Here, we developed a framework using Drosophila STARR-seq to create shape-matching filters based on meta-profiles of epigenetic features. We integrated these features with supervised machine-learning algorithms to predict enhancers. We further demonstrated that our model could be transferred to predict enhancers in mammals. We comprehensively validated the predictions using a combination of in vivo and in vitro approaches, involving transgenic assays in mice and transduction-based reporter assays in human cell lines (153 enhancers in total). The results confirmed that our model can accurately predict enhancers in different species without re-parameterization. Finally, we examined the transcription factor binding patterns at predicted enhancers versus promoters. We demonstrated that these patterns enable the construction of a secondary model that effectively distinguishes enhancers and promoters.
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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.