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[해외논문] A deep learning approach to evaluate the feasibility of enzymatic reactions generated by retrobiosynthesis

Biotechnology journal, v.16 no.5, 2021년, pp.2000605 -   

Kim, Yeji (Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering, KAIST Institute for BioCentury Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea) ,  Ryu, Jae Yong (Data Convergence Drug Research Center Korea Research Institute of Chemical Technology Daejeon Republic of Korea) ,  Kim, Hyun Uk (Systems Metabolic Engineering and Systems Healthcare Cross‐) ,  Jang, Woo Dae (Generation Collaborative Laboratory KAIST Daejeon Republic of Korea) ,  Lee, Sang Yup (Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering, KAIST Institute for BioCentury Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea)

Abstract AI-Helper 아이콘AI-Helper

AbstractRetrobiosynthesis allows the designing of novel biosynthetic pathways for the production of chemicals and materials through metabolic engineering, but generates a large number of reactions beyond the experimental feasibility. Thus, an effective method that can reduce a large number of the in...

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