Article

Ultra-fast variant effect prediction using biophysical transcription factor binding models

2024-06-30

Abstract excerpt

Sequence variation within TF binding sites can significantly affect TF-DNA interactions, influencing gene expression and contributing to disease susceptibility or phenotypic traits. Despite recent progress in deep sequence-to-function models that predict functional output from sequence data, these methods perform inadequately on some variant effect prediction tasks, especially with common genetic variants. This li...

Topics

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

Identifiers and source

Literature Corpus work: 9e605780-2a99-5aeb-a0ca-43bf15d51b03
DOI: 10.1101/2024.06.26.600873

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Ultra-fast variant effect prediction using biophysical transcription factor binding modelsDOI 10.1101/2024.06.26.600873Read

FABIAN-variant 2026: improved prediction of the effects of DNA variants on transcription factor binding.Semantic proximity Read

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

MAGGIE: leveraging genetic variation to identify DNA sequence motifs mediating transcription factor binding and function.Semantic proximity Read

Advancing regulatory variant effect prediction with AlphaGenome.Semantic proximity Read

Survey of variation in human transcription factors reveals prevalent DNA binding changes.Semantic proximity Read

motifbreakR: an R/Bioconductor package for predicting variant effects at transcription factor binding sites.Semantic proximity Read

Predicting the effects of SNPs on transcription factor binding affinitySemantic proximity Read

Comparative analysis of models in predicting the effects of SNPs on TF-DNA binding using large-scale in vitro and in vivo data.Semantic proximity Read

Prediction of Transcription Factor DNA Binding Affinity with High-Throughput <i>K</i> <sub>d</sub> Measurements and Deep LearningSemantic proximity Read

FABIAN-variant: predicting the effects of DNA variants on transcription factor binding.Semantic proximity Read

Evaluating the impact of single nucleotide variants on transcription factor binding.Semantic proximity Read

ChromBPNet: bias factorized, base-resolution deep learning models of chromatin accessibility reveal cis-regulatory sequence syntax, transcription factor footprints and regulatory variantsSemantic proximity Read