Kevin Sung

This study uses CRISPR-Cas9 to identify LY6E as an antiviral factor against coronaviruses in respiratory cells.

This study uses deep learning to detect entrenchment in antibody germline genes, revealing epistatic constraints from both intra-chain and genetically uncoupled partners.

This paper introduces a model that separates mutation and selection processes in antibody language models to improve prediction of mutation effects on antibody function.

This study compares nucleotide context models and protein language models for predicting antibody affinity maturation, finding nucleotide-based models perform better.

The paper develops 'thrifty' models of somatic hypermutation using convolutions on 3-mer embeddings, showing they outperform 5-mer models with fewer parameters.

The paper uses allelic inclusion data to train models that identify antibody sequence constraints, finding stronger correlations with antibody properties than existing methods.

This paper identifies diverse functional antibodies targeting the S2 subunit of SARS-CoV-2 spike, including one with broad neutralization activity across multiple coronaviruses.