Yuncheng Duan

The paper creates a pan-cancer catalog of mutation patterns at transcription factor binding sites across 15 tissue types, revealing enrichment in nearly one third of TF-binding site pairs.

PRIME is a Bayesian model that improves estimation of sub-genic intolerance by sharing information across regions, identifying disease-critical protein regions and enhancing variant interpretation.

This study quantifies intrinsic dCas9-DNA recognition using TANGO, identifying key factors affecting gRNA performance and revealing new aspects of dCas9 specificity.

The paper introduces BlueSTARR, a predictive modeling framework trained on whole-genome STARR-seq data to assess variant effects on regulatory functions, revealing purifying selection against loss-of-function and gain-of-function variants.

This paper introduces CATMINT, a method to estimate gene-level intolerance across variant categories, showing it outperforms existing metrics and reveals category-specific intolerance patterns in disease genes.

This study shows that adjusting for ancestry improves genome-wide estimates of regional intolerance by incorporating demographic history, leading to better variant classification.