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WP3 - IMPROWINE (Task 3.3. Modelling at fermenter scale: Individual Model…
WP3 - IMPROWINE
Task 3.3. Modelling at fermenter scale: Individual Model Based approach
Modelling yeast growth
Predictive microbiology Competition/Cooperation
Role of temperature
Role of initial inoculum
Modelling external metabolites
Kinetic model - single cultures
Hypotheses: assimilable Ni, Glx and Fruc to Ethanol and Glycerol; inhibition; lag-phase
T73 - CR85
Modelling fermenter
Distributed parameter system; reconciled with data; heat generation; temperature control
IMB vs Fokker Planck Equations
Possibility of recovering individual cell data from size distributioon measurements - validated with bacteria
PUBLICATIONS
Bioinformatics, 2016
Mathematical biosciences, 2017
Submitted or In preparation
Frontiers Microbiology - Fokker Planck
Bioinformatics - software Stochastic
Frontiers in Microbiology - Joint paper - Growth
Biotechnology & Bioengineering - Joint paper - External metabolites
Automatica - CRNT
Bioinformatics - Inverse DO
Theoretical Biology, 2017
Task 3.1. Systematic methods and tools for data-based model building.
AMIGO 2
Experimental Desing Techniques
To find optimal experimental conditions for modeling
On-line closed loop implementation. GAL network in yeast.
DFBA methods
To find time dependent fluxes attending to a biological objective
Inverse Dynamic Optimisatio
n
To simultaneously estimate parameters and fluxes --- to fit experimental data
Stochastic modelling techniques
Model - Stochastic simulation of gene regulatory networks
Software
Task 3.2. Modelling at cell scale: Systems biology approach
Read reference literature