Jayoung Ryu

This paper uses prime editing to classify LDLR variants by measuring their impact on LDL-C uptake, reclassifying many previously unclassified variants.

This paper improves variant effect quantification in base editing screens by integrating genotypic and phenotypic data using a Bayesian network called BEAN.

SIMBA is a graph embedding method that jointly embeds single cells and their features into a common space, enabling diverse single-cell analysis tasks.

The paper identifies a new class of super-enhancers active across multiple cell/tissue types and links them to fast-recovering 3D chromatin loops.