David K. Yang

mamp-ml: A deep learning approach to epitope immunogenicity in plants

The paper introduces mamp-ml, a deep learning model predicting plant receptor-ligand interactions using sequence data and ESM-2, achieving 73% accuracy without experimental structures.

Designing viral diagnostics with model-based optimization

This paper designs viral diagnostics using a model-based optimization approach, achieving higher sensitivity and specificity across viral genomic variation.

Genome-wide functional screen of 3'UTR variants uncovers causal variants for human disease and evolution

The paper identifies causal 3'UTR variants linked to human disease and evolution using a new high-throughput assay and functional analysis.

Capturing diverse microbial sequence with comprehensive and scalable probe design

The paper introduces CATCH, a method for designing compact and scalable probe sets to enhance metagenomic sequencing sensitivity, demonstrating improved viral genome recovery and diversity preservation.