Deep learning for metabolic pathway design.

Ryu, Gahyeon; Kim, Gi Bae; Yu, Taeho; Lee, Sang Yup

Ryu, Gahyeon; Kim, Gi Bae; Yu, Taeho; Lee, Sang Yup.

Afiliación

Ryu G; Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering (BK21 Four), KAIST Institute for BioCentury, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea; Systems Metabolic Engineering and Syste
Kim GB; Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering (BK21 Four), KAIST Institute for BioCentury, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea; Systems Metabolic Engineering and Syste
Yu T; Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering (BK21 Four), KAIST Institute for BioCentury, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea; Systems Metabolic Engineering and Syste
Lee SY; Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering (BK21 Four), KAIST Institute for BioCentury, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea; Systems Metabolic Engineering and Syste

Metab Eng ; 80: 130-141, 2023 Nov.

Article en En | MEDLINE | ID: mdl-37734652

Asunto(s)

Aprendizaje Profundo; Ingeniería Metabólica; Ingeniería Metabólica/métodos; Redes y Vías Metabólicas/genética

Palabras clave

Deep learning; Enzyme discovery; Machine learning; Metabolic pathway design; Systems metabolic engineering

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Ingeniería Metabólica / Aprendizaje Profundo Tipo de estudio: Prognostic_studies Idioma: En Revista: Metab Eng Asunto de la revista: ENGENHARIA BIOMEDICA / METABOLISMO Año: 2023 Tipo del documento: Article

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