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Machine Learning Empowering Microbial Cell Factory: A Comprehensive Review
Dechun Kong1, Jinyi Qian2, Cong Gao3
1School of Food Science and Pharmaceutical Engineering, Nanjing Normal University, Nanjing, 210023, People's Republic of China.
Abstract:
The wide application of machine learning has provided more possibilities for biological manufacturing, and the combination of machine learning and synthetic biology technology has ignited even more brilliant sparks, which has created an unpredictable value for the upgrading of microbial cell factories. The review delves into the synergies between machine learning and synthetic biology to create research worth investigating in biotechnology. We explore relevant databases, toolboxes, and machine learning-derived models. Furthermore, we examine specific applications of this combined approach in chemical production, human health, and environmental remediation. By elucidating these successful integrations, this review aims to provide valuable guidance for future research at the intersection of biomanufacturing and artificial intelligence.
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