Automation and machine learning drive rapid optimization of isoprenol production in Pseudomonas putida
Abstract Advances in genome engineering have improved our ability to perturb microbial metabolic networks, yet bioproduction campaigns often struggle with parsing complex metabolic datasets to efficiently enhance product titers. We address this challenge by coupling laboratory automation with machin...
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| Główni autorzy: | , , , , , , , , , , , , , , , |
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| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
Nature Portfolio
2025-12-01
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| Seria: | Nature Communications |
| Dostęp online: | https://doi.org/10.1038/s41467-025-66304-8 |
| Etykiety: |
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