Evan Komp

The paper uses machine learning to guide cell-free expression of carbonic anhydrases, identifying variants with improved stability under high temperatures.

This paper introduces NOMELT, a neural machine translation model that designs high-temperature stable proteins by learning thermophilicity from protein homologous pairs.

The paper curates a large dataset of protein-temperature pairs and demonstrates its potential for deep learning to improve thermal stability design.