Ryan Chung

This study fine-tunes sequence-to-expression models on personal genome and transcriptome data, showing improved performance on seen genes but not on unseen genes.

This study performs a genome-wide association study for Long COVID, identifying a significant association with the FOXP4 locus and highlighting the role of pulmonary dysfunction and COVID-19 severity.

The paper evaluates missense variant effect predictors using CAGI6 data, finding strong performance across settings and highlighting biases in some predictors.

This paper identifies genetic variants in tubule epithelial regulatory elements that explain most heritable differences in human kidney function using GWAS, scATAC-seq, and functional assays.

The paper evaluates deep learning models for predicting chromatin accessibility and finds reduced performance in cell type-specific regions, suggesting strategies to improve accuracy.

This study evaluates genomic deep learning models' ability to explain individual expression variation and finds limited performance.

This study quantifies how aging and genetics influence gene expression across 27 human tissues, finding tissue-specific differences in their contributions and identifying signatures of aging and selection.