Scientific Development Research

The intelligent design of metabolic pathways in microbial cell factories based on AI prediction achieves accurate prediction and optimization of metabolic flux by integrating multi-omics data with machine learning models, thereby improving the synthesis efficiency of target products. Centered on metabolic network modeling, this study combines deep learning algorithms to identify key nodes and design regulatory strategies, thus constructing efficient and stable cell factories. In the experimental verification stage, the modification of specific metabolic pathways significantly improved product yield and conversion efficiency, verifying the feasibility and superiority of AI prediction in guiding metabolic engineering. This method not only provides a new intelligent design idea for industrial biomanufacturing but also lays a technical foundation for future green and sustainable production.

AI prediction; Microbial cell factory; Metabolic pathway design; Multi-omics data; Metabolic engineering