ArticleBioinformatics (Oxford, England)2019
Integrating regulatory DNA sequence and gene expression to predict genome-wide chromatin accessibility across cellular contexts.
Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.
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Who cites it
47 citing papers in PubMed.
- Chromatin Accessibility Reveals Adaptive Regulatory Variation in a Keystone Freshwater Fish.Molecular ecology · 2026Article
- Toward generalizable and interpretable AI in regulatory genomics.Nature genetics · 2026Review
- Context-aware sequence-to-function model of human gene regulation.Nature communications · 2026Article
- Cell type annotation for scATAC-seq via DNA large language model and graph domain adaptation.PLoS computational biology · 2026Article
- Quantifying the impact of genetic mutations on enhancer dynamics.bioRxiv : the preprint server for biology · 2025Article
- Predicting sequence-specific amplification efficiency in multi-template PCR with deep learning.Nature communications · 2025Article
- Comprehensive molecular impact mapping of common and rare variants at GWAS loci.bioRxiv : the preprint server for biology · 2025Article
- Recipes and ingredients for deep learning models of 3D genome folding.Current opinion in genetics & development · 2025Review
- A multi-modal transformer for cell type-agnostic regulatory predictions.Cell genomics · 2025Article
- ChromBPNet: bias factorized, base-resolution deep learning models of chromatin accessibility reveal cis-regulatory sequence syntax, transcription factor footprints and regulatory variants.bioRxiv : the preprint server for biology · 2025Article
- Predicting chromatin conformation contact maps.PloS one · 2025Article
- Dynamic Chromatin Accessibility and Gene Expression Regulation During Maize Leaf Development.Genes · 2024Article
- EpiGePT: a pretrained transformer-based language model for context-specific human epigenomics.Genome biology · 2024Article
- Identifying transcription factors with cell-type specific DNA binding signatures.BMC genomics · 2024Article
- CREaTor: zero-shot cis-regulatory pattern modeling with attention mechanisms.Genome biology · 2023Article
- Systematic differences in discovery of genetic effects on gene expression and complex traits.Nature genetics · 2023Article
- Predictive analyses of regulatory sequences with EUGENe.Nature computational science · 2023Article
- GoM DE: interpreting structure in sequence count data with differential expression analysis allowing for grades of membership.Genome biology · 2023Article
- GoM DE: interpreting structure in sequence count data with differential expression analysis allowing for grades of membership.bioRxiv : the preprint server for biology · 2023Article
- Prediction of G4 formation in live cells with epigenetic data: a deep learning approach.NAR genomics and bioinformatics · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
motivationGenome-wide profiles of chromatin accessibility and gene expression in diverse cellular contexts are critical to decipher the dynamics of transcriptional regulation. Recently, convolutional neural networks have been used to learn predictive cis-regulatory DNA sequence models of context-specific chromatin accessibility landscapes. However, these context-specific regulatory sequence models cannot generalize predictions across cell types.
resultsWe introduce multi-modal, residual neural network architectures that integrate cis-regulatory sequence and context-specific expression of trans-regulators to predict genome-wide chromatin accessibility profiles across cellular contexts. We show that the average accessibility of a genomic region across training contexts can be a surprisingly powerful predictor. We leverage this feature and employ novel strategies for training models to enhance genome-wide prediction of shared and context-specific chromatin accessible sites across cell types. We interpret the models to reveal insights into cis- and trans-regulation of chromatin dynamics across 123 diverse cellular contexts. AVAILABILITY AND IMPLEMENTATION: The code is available at https://github.com/kundajelab/ChromDragoNN. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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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.