Machine Learning, Computational Biology, Protein Engineering, Bioinformatics.
with two core examples: engineering GFP fluorescence, and engineering TEM-1 Beta-lactamase. In both cases, only 24 or 96 examples are sufficient as training data for exploring the fitness landscape of each protein. What is really impressive is the fact that the mutations found with this approach