Recent advances in constraint and machine learning-based metabolic modeling by leveraging stoichiometric balances, thermodynamic feasibility and kinetic law formalisms.

Suthers, Patrick F; Foster, Charles J; Sarkar, Debolina; Wang, Lin; Maranas, Costas D

Suthers, Patrick F; Foster, Charles J; Sarkar, Debolina; Wang, Lin; Maranas, Costas D.

Afiliação

Suthers PF; Department of Chemical Engineering, The Pennsylvania State University, University Park, PA, USA; DOE Center for Advanced Bioenergy and Bioproducts Innovation, The Pennsylvania State University, University Park, PA, USA.
Foster CJ; Department of Chemical Engineering, The Pennsylvania State University, University Park, PA, USA.
Sarkar D; Department of Chemical Engineering, The Pennsylvania State University, University Park, PA, USA.
Wang L; Department of Chemical Engineering, The Pennsylvania State University, University Park, PA, USA.
Maranas CD; Department of Chemical Engineering, The Pennsylvania State University, University Park, PA, USA; DOE Center for Advanced Bioenergy and Bioproducts Innovation, The Pennsylvania State University, University Park, PA, USA. Electronic address: costas@psu.edu.

Metab Eng ; 63: 13-33, 2021 01.

Article em En | MEDLINE | ID: mdl-33310118

Assuntos

Aprendizado de Máquina; Modelos Biológicos; Estudos de Viabilidade; Cinética; Termodinâmica

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Aprendizado de Máquina / Modelos Biológicos Tipo de estudo: Prognostic_studies Idioma: En Revista: Metab Eng Assunto da revista: ENGENHARIA BIOMEDICA / METABOLISMO Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

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