Large scale active-learning-guided exploration for in vitro protein production optimization
Résumé
Lysate-based cell-free systems have become a major platform to study gene expression but batch-to-batch variation makes protein production difficult to predict. Here we describe an active learning approach to explore a combinatorial space of~4,000,000 cell-free buffer 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.
Origine : Publication financée par une institution
licence : CC BY - Paternité
licence : CC BY - Paternité
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