graphical abstract

D2D data facilitates evaluation of computational tools

Recent study uses student-generated data to examines predictive efficacy of a suite of computational tools to better model enzyme thermal stability  

Huang, P., Chu, S. K., Frizzo, H. N., Connolly, M. P., Caster, R. W., & Siegel, J. B. (2020). Evaluating Protein Engineering Thermostability Prediction Tools Using an Independently Generated Dataset. ACS omega5(12), 6487-6493. https://pubs.acs.org/doi/abs/10.1021/acsomega.9b04105