Young Su Ko

The paper benchmarks text-integrated protein language models and introduces embedding fusion to improve performance across diverse tasks.

RESP2 is an AI pipeline for antibody discovery that optimizes multiple properties and targets, achieving high success rates in binding affinity and specificity.

ProteinAligner improves protein function and property prediction by integrating sequence, structure, and literature text modalities in a multi-modal pretraining framework.

Raygun is a generative AI framework that miniaturizes, modifies, and expands proteins while preserving function and structural integrity, validated through cell-based experiments.

TUnA is a Transformer model that predicts protein-protein interactions from sequence data and provides uncertainty estimates for unseen sequences, improving reliability.