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Volumn 33, Issue , 2016, Pages 158-168

ISCHRUNK - In Silico Approach to Characterization and Reduction of Uncertainty in the Kinetic Models of Genome-scale Metabolic Networks

Author keywords

Enzyme saturations; Kinetic parameters; Large scale kinetic models; Machine learning; Monte Carlo sampling; Uncertainty reduction

Indexed keywords

ARTIFICIAL INTELLIGENCE; ENZYMES; ESCHERICHIA COLI; KINETIC PARAMETERS; KINETIC THEORY; KINETICS; LEARNING SYSTEMS; METABOLISM; METABOLITES; MONTE CARLO METHODS; PHYSIOLOGY; THERMODYNAMICS; UNCERTAINTY ANALYSIS;

EID: 84952637898     PISSN: 10967176     EISSN: 10967184     Source Type: Journal    
DOI: 10.1016/j.ymben.2015.10.002     Document Type: Article
Times cited : (65)

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