Sang-Cheol Seok

This paper introduces a classification-based generative approach to optimize closed-loop tACS during sleep by targeting global slow oscillations, showing potential for improving memory consolidation.

The paper shows that penetrance estimates for rare variants can be unreliable due to ascertainment bias and introduces PenEst, an app to analyze this effect, along with LOD score corrections for pathogenicity assessment.

This paper conducts a genome-wide association study to identify genetic modifiers of disease severity in dystrophinopathy patients, finding multiple candidate loci associated with age at loss of ambulation.

The paper applies functional genomic datasets to six top GWAS loci to identify candidate gene modifiers of dystrophinopathy severity.

The paper evaluates the TE-PPLD method for GWAS of time-to-event phenotypes in small to moderate sample sizes, showing advantages over Cox Proportional Hazards analysis.