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The fitted function describes the pH-drop during 'forward'-shift experiments and the increase of the pH during 'reverse'-shift experiments. The estimated parameters are used to compute the changing pH level in the models of the pH.induced metabolic shift in continuous cultures under phosphate limitation of C. acetobutylicum. Furthermore, the parameters can be applied to join different independent experiments into a single data set.
To fit the changing pH level, an exponential function and a ...
Creator: Thomas Millat
Submitter: Thomas Millat
Model type: Not specified
Model format: Matlab package
Environment: Matlab
First darft of a model including glycolysis and the transcription and translation of the enzymes. See the datafile "Information on the darft transcription/translation model." for information.
Creator: Fiona Achcar
Submitter: Fiona Achcar
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: Not specified
Using optical tweezers to position yeast cells in a microfluidic chamber, we were able to observe sustained oscillations in individual isolated cells. Using a detailed kinetic model for the cellular reactions, we simulated the heterogeneity in the response of the individual cells, assuming small differences in a single internal parameter. By operating at two different flow rates per experiment, we observe four of categories of cell behaviour. The present model (gustavsson4) predicts the steady-state ...
Creators: Franco du Preez, Jacky Snoep, Dawie van Niekerk
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
The model includes glycolysis, pentosephosphate pathway, purine salvage reactions, purine de novo synthesis, redox balance and biomass growth. The network balances adenylate pool as opened moiety.
Creator: Maksim Zakhartsev
Submitter: Maksim Zakhartsev
Model type: Metabolic network
Model format: SBML
Environment: Copasi
Using optical tweezers to position yeast cells in a microfluidic chamber, we were able to observe sustained oscillations in individual isolated cells. Using a detailed kinetic model for the cellular reactions, we simulated the heterogeneity in the response of the individual cells, assuming small differences in a single internal parameter. By operating at two different flow rates per experiment, we observe four of categories of cell behaviour. The present model (gustavsson1) predicts the limit ...
Creators: Franco du Preez, Jacky Snoep, David D van Niekerk
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
Using optical tweezers to position yeast cells in a microfluidic chamber, we were able to observe sustained oscillations in individual isolated cells. Using a detailed kinetic model for the cellular reactions, we simulated the heterogeneity in the response of the individual cells, assuming small differences in a single internal parameter. By operating at two different flow rates per experiment, we observe four of categories of cell behaviour. The present model (gustavsson2) predicts the damped ...
Creators: Franco du Preez, Jacky Snoep, David D van Niekerk
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
Using optical tweezers to position yeast cells in a microfluidic chamber, we were able to observe sustained oscillations in individual isolated cells. Using a detailed kinetic model for the cellular reactions, we simulated the heterogeneity in the response of the individual cells, assuming small differences in a single internal parameter. By operating at two different flow rates per experiment, we observe four of categories of cell behaviour. The present model (gustavsson3) predicts the steady-state ...
Creators: Franco du Preez, Jacky Snoep, David D van Niekerk
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
An existing detailed kinetic model for the steady-state behavior of yeast glycolysis was tested for its ability to simulate dynamic behavior. This model (dupreez1) is the basis kinetic model derived from that published by Teusink et al., 2000 (PMID: 10951190).
Creators: Franco du Preez, David D van Niekerk
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
An existing detailed kinetic model for the steady-state behavior of yeast glycolysis was tested for its ability to simulate dynamic behavior. This model (dupreez2) is an oscillating version of the basis kinetic model (dupreez1) derived from that published by Teusink et al., 2000 (PMID: 10951190).
Creators: Franco du Preez, Jacky Snoep, David D van Niekerk
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
An existing detailed kinetic model for the steady-state behavior of yeast glycolysis was tested for its ability to simulate dynamic behavior. This model (dupreez3) is an oscillating version of the model published by Teusink et al., 2000 (PMID: 10951190), which describes data for glycolytic intermediates in oscillating yeast cultures reported by Richard et al., 1996 (PMID: 8813760).
Creators: Franco du Preez, Jacky Snoep, David D van Niekerk
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
An existing detailed kinetic model for the steady-state behavior of yeast glycolysis was tested for its ability to simulate dynamic behavior. This model (dupreez4) is an oscillating version of the model published by Teusink et al., 2000 (PMID: 10951190), which describes data for glycolytic intermediates in oscillating yeast cultures reported by Richard et al., 1996a (PMID: 8813760) as well as the rapid synchronization following the mixing of two yeast cultures that oscillate 180 degrees out of ...
Creators: Franco du Preez, Jacky Snoep, David D van Niekerk
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
An existing detailed kinetic model for the steady-state behavior of yeast glycolysis was tested for its ability to simulate dynamic behavior. This model (dupreez5) is an oscillating version of the model published by Teusink et al., 2000 (PMID: 10951190), which describes the amplitude bifurcation of oscillating yeast cultures in a CSTR setup reported by Hynne et al., 2001 (PMID: 11744196).
Creators: Franco du Preez, Jacky Snoep, David D van Niekerk
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
An existing detailed kinetic model for the steady-state behavior of yeast glycolysis was tested for its ability to simulate dynamic behavior. This model (dupreez6) is an oscillating version of the model published by Teusink et al., 2000 (PMID: 10951190), which describes data for glycolytic intermediates in cell free extracts of oscillating yeast cultures reported by Das and Busse, 1991 (PMCID: 1260073).
Creators: Franco du Preez, Jacky Snoep, David D van Niekerk
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
An existing detailed kinetic model for the steady-state behavior of yeast glycolysis was tested for its ability to simulate dynamic behavior. This model (dupreez7) is an oscillating version of the model published by Teusink et al., 2000 (PMID: 10951190), which describes the fluorescence signal of NADH in oscillating yeast cultures reported by Nielsen et al., 1998 (PMID: 17029704).
Creators: Franco du Preez, Jacky Snoep, David D van Niekerk
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
The zip file contains model files and an experiment file. Unpack it in a directory and navigate with matlab to there. Use the 'matlab_execution_guide.m' for simulation and visualisation of the model. This file is written in matlab cell mode, so it is not a stand alone function.
Three models have been developed to test their capacity to reproduce the experimental data from Study: 'Controlled sigmaB induction in shake flask' with Assay: 'IPTG induction of sigmaB in BSA115'. One model assumes a ...
Creator: Ulf Liebal
Submitter: Ulf Liebal
Model type: Ordinary differential equations (ODE)
Model format: Matlab package
Environment: Matlab
input: array of investigated quenching temperatures and volumetric flows output: quenching time and coil length as function of quenching temperature, and quenching time as function of temperature for varying coil lengths
Creator: Sebastian Curth
Submitter: Sebastian Curth
Model type: Algebraic equations
Model format: Matlab package
Environment: Matlab
The kinetic model includes sugar uptake, degradation of glucose into pyruvate and the fermentation of pyruvate.
Creator: Jennifer Levering
Submitter: Jennifer Levering
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: JWS Online
The kinetic model includes sugar uptake, degradation of glucose into pyruvate and the fermentation of pyruvate.
Creators: Jennifer Levering, Mark Musters
Submitter: Jennifer Levering
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: JWS Online
The zip-folder contains files for execution in matlab that allow for the simulation of stressosome dynamics and reproduction of published data on the stressosome. The important file for execution is 'liebal_stressosome-model_12_workflow-matlab.m'.
Creator: Ulf Liebal
Submitter: Ulf Liebal
Model type: Agent based modelling
Model format: Matlab package
Environment: Matlab
Quorum sensing(QS) allows the bacteria to monitor their surroundings and the size of their population. Staphylococcus aureus makes use of QS to regulate the production of virulence factors. This mathematical model of the QS system in S aureus was presented and analyzed (Journal of Mathematical Biology(2010) 61:17–54) in order to clarify the roles of the distinct interactions that make up the QS process, demonstrating which reactions dominate the behaviour of the system at various timepoints. ...
Creators: Sara Jabbari, John King, Adrian Koerber, Paul Williams
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
An ODE model representing the metabolic network governing acid and solvent production by Clostridium acetobutylicum (Haus et al. BMC Systems Biology 2011, 5:10), incorporating the effect of pH upon gene regulation and subsequent end-product levels. This model describes the third of four experiments in which the pH of the culture was shifted. For this experiment acidogenesis at pH 5.7 was maintained for 121 hours, after which the pH control was stopped, allowing the natural metabolic shift to the ...
Creators: Sara Jabbari, Sylvia Haus
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
An ODE model representing the metabolic network governing acid and solvent production by Clostridium acetobutylicum (Haus et al. BMC Systems Biology 2011, 5:10), incorporating the effect of pH upon gene regulation and subsequent end-product levels. This model describes the last of four experiments in which the pH of the culture was shifted. For this experiment the pH shift was reversed compared to the first three (shift from pH 4.5 to 5.7), with the pH control switched off after 129 hours. ...
Creators: Sara Jabbari, Sylvia Haus
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
An ODE model representing the metabolic network governing acid and solvent production by Clostridium acetobutylicum (Haus et al. BMC Systems Biology 2011, 5:10), incorporating the effect of pH upon gene regulation and subsequent end-product levels. This model describes the second of four experiments in which the pH of the culture was shifted. For this experiment acidogenesis at pH 5.7 was maintained for 137.5 hours, after which the pH control was stopped, allowing the natural metabolic shift to ...
Creators: Sara Jabbari, Sylvia Haus
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
An ODE model representing the metabolic network governing acid and solvent production by Clostridium acetobutylicum (Haus et al. BMC Systems Biology 2011, 5:10), incorporating the effect of pH upon gene regulation and subsequent end-product levels. This model describes the first of four experiments in which the pH of the culture was shifted. For this experiment acidogenesis at pH 5.7 was maintained for 137 hours, after which the pH control was stopped, allowing the natural metabolic shift to the ...
Creators: Sara Jabbari, Sylvia Haus
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
Bacillus subtilis cells may opt to forgo normal cell division and instead form spores if subjected to certain environmental stimuli, for example nutrient deficiency or extreme temperature. The gene regulation net-work governing sporulation initiation accordingly incorporates a variety of signals and is of significant complexity. The present model (Bulletin of Mathematical Biology (2011) 73:181–211) includes four of these signals: nutrient levels, DNA damage, the products of the competence genes, ...
Creators: Sara Jabbari, John Heap, John King
Submitter: Franco du Preez
Model type: Ordinary differential equations (ODE)
Model format: Not specified
Environment: JWS Online
Fixed parameter model, where the glycolysis model of bloodstream form T. brucei is extended with the pentose phosphate pathway and a ribokinase in the glycosome. Non-final version.
Creators: Eduard Kerkhoven, Fiona Achcar
Submitter: Eduard Kerkhoven
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: Copasi
Fixed parameter model, where the glycolysis model of bloodstream form T. brucei is extended with the pentose phosphate pathway and an ATP:ADP antiporter over the glycosomal membrane. Non-final version.
Creators: Eduard Kerkhoven, Fiona Achcar
Submitter: Eduard Kerkhoven
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: JWS Online
SBML file supplementary material of the publication.
Creators: Fiona Achcar, Barbara Bakker, Mike Barrett, Rainer Breitling, Eduard Kerkhoven
Submitter: Fiona Achcar
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: Not specified
The model describes the electron transport chain (ETC) of Escherichia coli by ordinary differential equations. Also a simplified growth model based on an abstract reducing potential describing the balance of electron donor (glucose) and electron acceptors is coupled to the ETC. The model should reproduce and predict the regulation of the described system for different oxygen availability within the aerobiosis scale (glucose limited continuous culture<=>chemostat). Therefore oxygen is changed ...
Creator: Sebastian Henkel
Submitter: Sebastian Henkel
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: JWS Online
A model of E. coli central carbon core metabolism, used as starting point for B. subtilis modelling. It is developed by Chassagnole et al. doi:10.1002/bit.10288.
Creators: Ulf Liebal, Fei He
Submitter: Ulf Liebal
Model type: Ordinary differential equations (ODE)
Model format: SBML
Environment: Not specified