A large-scale exploration of cell-free compositions to maximize protein production using active learning
Résumé
Lysate-based cell-free systems have become a major platform to study gene expression 1-3 but batch-to-batch variation makes protein production difficult to predict 4. Here we describe an active learning approach 5 to explore a combinatorial space of ~4,000,000 cell-free compositions, maximizing protein production and identifying critical parameters involved in cell-free productivity. We also provide a one-step-method to achieve high quality predictions for protein production using minimal experimental effort regardless of the lysate quality.
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