Franco du Preez

The main objectives of SysMO-DB are to: facilitate the web-based exchange of data between research groups within- and inter- consortia, and to provide an integrated platform for the dissemination of the results of the SysMO projects to the scientific community. We aim to devise a progressive and scalable solution to the data management needs of the SysMO initiative, that:

• facilitates and maximises the potential for data exchange between SysMO research groups;
• maximises the ‘shelf life’ and ...

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 ...

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 ...

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 ...

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 ...

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).

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).

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).

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 ...

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).

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).

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).

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. ...

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 ...

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. ...

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 ...

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 ...

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, ...

An overview of the JWS Online system, with emphasis on the latest model simulation interface and an update on the SBGN-ML and SED-ML support currently under development.

SEEK at ICSB 2012 (presented by Olga Krebs)