Transfer learning improves predictions of enzyme kinetic parameters

Abstract

In this issue of Chem Catalysis, Shen and colleagues present a novel model architecture and training technique for predicting enzyme kinetic parameters. The proposed models are an important step toward the development of more accurate kinetic prediction models, which are needed for many important industrial and scientific applications.