Lien vers Pubmed [PMID] – 32312991
Nat Commun. 2020 Apr 20;11(1):1872
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.
Behind the paper : https://bioengineeringcommunity.nature.com/users/382588-olivier-borkowski/posts/66375-active-learning-leads-to-highly-efficient-predictions-in-cell-free-systems