Younghun Han

The paper introduces a machine learning framework to detect high-order genetic interactions in GWAS by encoding decision paths from classification trees as features, improving model accuracy and interpretability.

The paper constructs a single-cell eQTL dataset from Asian never-smokers, identifying alveolar cell-specific genes linked to lung cancer susceptibility.

This study identifies smoking-associated natural killer cell subsets in NSCLC that correlate with survival and response to neoadjuvant chemoimmunotherapy, suggesting their use in therapeutic stratification.

The paper develops polygenic risk scores to stratify lung cancer and smoking cessation risk, showing significant odds ratios in diverse populations and planning clinical trials to evaluate interventions.

The paper identifies twelve novel genetic risk loci for lung cancer subtypes through multi-ancestry GWAS and shows smoking-independent genetic risk.

The paper identifies cell-type specific lung cancer susceptibility genes by integrating single-cell multi-omics data with GWAS loci.

This study identifies 13 genome-wide significant loci associated with SARS-CoV-2 infection or severe COVID-19 through a global meta-analysis of 49,562 patients.

This study quantifies genetic correlations between six solid cancers and other diseases using GWAS data, finding shared heritability and functional enrichment in regulatory regions.