L Dornfeld

A structure-conditioned nucleotide-level Potts model designs protein and coding sequences jointly, enabling tRNA adaptation and RNA motif embedding beyond synonymous codons with designability comparable to Caliby.

This study benchmarks ligand-conditioned protein generation using sequence-only data, revealing trade-offs between diversity and foldability based on dataset characteristics.

This paper introduces Rho-tag and SiR-tag, fast, reversible, and fluorogenic protein tags for live-cell imaging, compatible with super-resolution techniques and demonstrated in zebrafish larvae.

The paper predicts homo-oligomerization across four proteomes using AlphaFold2, finding that 50% of archaea, 45% of bacteria, and 20% of eukaryotes form homomers, with disease mutations enriched at interfaces.

This study designs soluble analogues of integral membrane proteins using deep learning, achieving high thermal stability and functional accuracy.