Article

CoRE-ATAC: A deep learning model for the functional classification of regulatory elements from single cell and bulk ATAC-seq data

2020-06-23

Abstract excerpt

Cis -Regulatory elements (cis-REs) include promoters, enhancers, and insulators that regulate gene expression programs via binding of transcription factors. ATAC-seq technology effectively identifies active cis -REs in a given cell type (including from single cells) by mapping accessible chromatin at base-pair resolution. However, these maps are not immediately useful for inferring specific functions of cis -RE...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 5ab84054-4c62-5e11-adf6-8ba371468b0b
DOI: 10.1101/2020.06.22.165183

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

CoRE-ATAC: A deep learning model for the functional classification of regulatory elements from single cell and bulk ATAC-seq dataDOI 10.1101/2020.06.22.165183Read

Mapping enhancer-gene regulatory interactions from single-cell dataSemantic proximity Read

AtacWorks: A deep convolutional neural network toolkit for epigenomicsSemantic proximity Read

Single cell ATAC-seq in human pancreatic islets and deep learning upscaling of rare cells reveals cell-specific type 2 diabetes regulatory signaturesSemantic proximity Read

maxATAC: genome-scale transcription-factor binding prediction from ATAC-seq with deep neural networksSemantic proximity Read

Single-cell ATAC-Seq in human pancreatic islets and deep learning upscaling of rare cells reveals cell-specific type 2 diabetes regulatory signatures.Semantic proximity Read

Current genomic deep learning models display decreased performance in cell type specific accessible regionsSemantic proximity Read

REnformer, a single-cell ATAC-seq predicting model to investigate open chromatin sitesSemantic proximity Read

Discovering differential genome sequence activity with interpretable and efficient deep learningSemantic proximity Read

Decoding sequence determinants of gene expression in diverse cellular and disease statesSemantic proximity Read

UniversalEPI: robust prediction of cell type-specific and differential chromatin interactions from DNA sequence and chromatin accessibilitySemantic proximity Read

Tissue-specific enhancer-gene maps from multimodal single-cell data identify causal disease allelesSemantic proximity Read

Tissue-specific enhancer-gene maps from multimodal single-cell data identify causal disease alleles.Semantic proximity Read