Details
Title
Andreozzi, Stefano
Sciper ID
193203
Publications
Computational studies on Escherichia coli metabolism
Engineering improved productivity of 1,4-butanediol in E. coli – a kinetic modeling approach
Exploring enhancement of 1,4-butanediol production in recombinant E. coli using Large-scale kinetic models
Exploring enhancement of 1,4-butanediol production in recombinant E. coli using large-scale kinetic models
Identification of metabolic engineering targets for the enhancement of 1,4-butanediol production in recombinant E. coli using large-scale kinetic[...]
In silico analysis of the interplay between P/O ratio and physiological states of the optimally grown Escherichia coli
Metabolic control analysis of the central carbon pathway in optimally grown E. coli
iSCHRUNK – In Silico Approach to Characterization and Reduction of Uncertainty in the Kinetic Models of Genome-scale Metabolic Networks
iSCHRUNK – In Silico Approach to Characterization and Reduction of Uncertainty in the Kinetic Models of Genome-scale Metabolic Networks
iSCHRUNK – in Silico Approach to Characterization and Reduction of Uncertainty in the Kinetic Models of Genome-scale Metabolic Networks
Engineering improved productivity of 1,4-butanediol in E. coli – a kinetic modeling approach
Exploring enhancement of 1,4-butanediol production in recombinant E. coli using Large-scale kinetic models
Exploring enhancement of 1,4-butanediol production in recombinant E. coli using large-scale kinetic models
Identification of metabolic engineering targets for the enhancement of 1,4-butanediol production in recombinant E. coli using large-scale kinetic[...]
In silico analysis of the interplay between P/O ratio and physiological states of the optimally grown Escherichia coli
Metabolic control analysis of the central carbon pathway in optimally grown E. coli
iSCHRUNK – In Silico Approach to Characterization and Reduction of Uncertainty in the Kinetic Models of Genome-scale Metabolic Networks
iSCHRUNK – In Silico Approach to Characterization and Reduction of Uncertainty in the Kinetic Models of Genome-scale Metabolic Networks
iSCHRUNK – in Silico Approach to Characterization and Reduction of Uncertainty in the Kinetic Models of Genome-scale Metabolic Networks
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