Article

Multimodal learning of noncoding variant effects using genome sequence and chromatin structure

2022-12-21

Abstract excerpt

<h4>Motivation</h4> A growing amount of noncoding genetic variants, including single-nucleotide polymorphisms (SNPs), are found to be associated with complex human traits and diseases. Their mechanistic interpretation is relatively limited and can use the help from computational prediction of their effects on epigenetic profiles. However, current models often focus on local, 1D genome sequence determinants and di...

Topics

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

Identifiers and source

Literature Corpus work: 88bf0db9-e4be-5017-bdf6-c251b10814eb
DOI: 10.1101/2022.12.20.521331

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Multimodal learning of noncoding variant effects using genome sequence and chromatin structureDOI 10.1101/2022.12.20.521331Read

Deep learning approaches for non-coding genetic variant effect prediction: current progress and future prospects.Semantic proximity Read

DanQ: a hybrid convolutional and recurrent deep neural network for quantifying the function of DNA sequencesSemantic proximity Read

DanQ: a hybrid convolutional and recurrent deep neural network for quantifying the function of DNA sequences.Semantic proximity Read

Predicting effects of noncoding variants with deep learning-based sequence model.Semantic proximity Read

Effective gene expression prediction from sequence by integrating long-range interactionsSemantic proximity Read

Predicting the effect of non-coding mutations on single-cell DNA methylation using deep learningSemantic proximity Read

AlphaGenome: advancing regulatory variant effect prediction with a unified DNA sequence modelSemantic proximity Read

Predicting the regulatory impacts of noncoding variants on gene expression through epigenomic integration across tissues and single-cell landscapes.Semantic proximity Read

Functional Interpretation of Genetic Variants Using Deep Learning Predicts Impact on EpigenomeSemantic proximity Read

DeepFun: a deep learning sequence-based model to decipher non-coding variant effect in a tissue- and cell type-specific manner.Semantic proximity Read

Systematic Benchmarking of DNA Sequence Encoding Strategies for Predicting Regulatory Effects of Non-Coding SNPs.Semantic proximity Read

A sequence-based global map of regulatory activity for deciphering human geneticsSemantic proximity Read