Jae Hyeon Lee

deepNGS Navigator uses deep contrastive learning to visualize and analyze antibody sequence datasets, revealing clonal relationships and evolutionary patterns.

This paper introduces a machine learning framework for therapeutic antibody design that integrates computational methods with experimental validation, resulting in significantly improved binding affinity for multiple targets.

EquiFold predicts all-atom protein structures using an SE(3)-equivariant coarse-grained geometric representation without sequence alignments or language model embeddings, matching AlphaFold accuracy orders of magnitude faster in preliminary tests.