References of "Gilles, E. D"
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See detailAnalysis of an apoptotic core model focused on experimental design using artificial data.
Schlatter, R.; Conzelmann, H.; Gilles, E. D. et al

in IET Systems Biology (2009), 3(4), 255-65

The activation of caspases is a central mechanism in apoptosis. To gain further insights into complex processes like this, mathematical modelling using ordinary differential equations (ODEs) can be a very ... [more ▼]

The activation of caspases is a central mechanism in apoptosis. To gain further insights into complex processes like this, mathematical modelling using ordinary differential equations (ODEs) can be a very powerful research tool. Unfortunately, the lack of measurement data is a common problem in building such kinetic models, because it practically constrains the identifiability of the model parameters. An existing mathematical model of caspase activation during apoptosis was used in order to design future experimental setups that will help to maximise the obtained information. For this purpose, artificial measurement data are generated in silico to simulate potential experiments, and the model is fitted to this data. The model is also analysed using observability gramian and sensitivity analyses. The used analysis methods are compared. The artificial data approach allows one to make conclusions about system properties, identifiability of parameters and the potential information content of additional measurements for the used caspase activation model. The latter facilitates to improve the experimental design of further measurements significantly. The performed analyses reveal that several kinetic parameters are not at all, or only scarcely, identifiable, and that measurements of activated caspase 8 will maximally improve the parameter estimates. Furthermore, we can show that many assays with inhibitor of apoptosis protein (IAP) knockout cells only provide redundant information for our needs and as such do not have to be carried out. [less ▲]

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See detailModeling and experimental validation of the signal transduction via the Escherichia coli sucrose phospho transferase system.
Sauter, Thomas UL; Gilles, E. D.

in Journal of Biotechnology (2004), 110(2), 181-99

Bacterial signal processing was investigated concerning the sucrose phosphotransferase system (sucrose PTS) in the bacterium Escherichia coli as an example. The about 20 different phosphotransferase ... [more ▼]

Bacterial signal processing was investigated concerning the sucrose phosphotransferase system (sucrose PTS) in the bacterium Escherichia coli as an example. The about 20 different phosphotransferase systems (PTSs) of the cell fulfill besides the transport of various carbohydrates, also the function of one signal processing system. Extra- and intracellular signals are converted within the PTS protein chain to important regulatory signals affecting, e.g. carbon metabolism and chemotaxis. A detailed dynamical model of the sucrose PTS was developed describing transport and signal processing function. It was formulated using a detailed description of complex formation and phosphate transfer between the chain proteins. Model parameters were taken from literature or were identified with own experiments. Simulation studies together with experimental hints showed that the dynamic behavior of phosphate transfer in the PTS runs within 1 s. Therefore a description of steady state characteristics is sufficient for describing the signaling properties of the sucrose PTS. A steady state characteristic field describes the degree of phosphorylation of the PTS protein EIIACrr as a function of the input variables extracellular sucrose concentration and intracellular phosphoenolpyruvate (PEP):pyruvate ratio. The model has been validated with different experiments performed in a CSTR using a sucrose positive E. coli W3110 derivative. A method for determining intracellular metabolite concentrations has been developed. A sample preparation technique using a boiling ethanol buffer solution was successfully applied. The PTS output signal degree of phosphorylation of EIIACrr was also measured. Steady state conditions with varying dilution rate and dissolved oxygen concentration and dynamical variations applying different stimuli to the culture were considered. Pulse, and stop feeding experiments with limiting sucrose concentrations were performed. Simulation and experimental results matched well. The same holds for the expanded sucrose PTS and glycolysis model. [less ▲]

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See detailTime hierarchies in the Escherichia coli carbohydrate uptake and metabolism.
Kremling, A.; Fischer, S.; Sauter, Thomas UL et al

in Bio Systems (2004), 73(1), 57-71

The analysis of metabolic pathways with mathematical models contributes to the better understanding of the behavior of metabolic processes. This paper presents the analysis of a mathematical model for ... [more ▼]

The analysis of metabolic pathways with mathematical models contributes to the better understanding of the behavior of metabolic processes. This paper presents the analysis of a mathematical model for carbohydrate uptake and metabolism in Escherichia coli. It is shown that the dynamic processes cover a broad time span from some milliseconds to several hours. Based on this analysis the fast processes could be described with steady-state characteristic curves. A subsequent robustness analysis of the model parameters shows that the fast part of the system may act as a filter for the slow part of the system; the sensitivities of the fast system are conserved. From these findings it is concluded that the slow part of the system shows some robustness against changes in parameters of the fast subsystem, i.e. if a parameter shows no sensitivity for the fast part of the system, it will also show no sensitivity for the slow part of the system. [less ▲]

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See detailReduction of mathematical models of signal transduction networks: simulation-based approach applied to EGF receptor signalling.
Conzelmann, H.; Saez-Rodriguez, J.; Sauter, Thomas UL et al

in Systems biology (2004), 1(1), 159-69

Biological systems and, in particular, cellular signal transduction pathways are characterised by their high complexity. Mathematical models describing these processes might be of great help to gain ... [more ▼]

Biological systems and, in particular, cellular signal transduction pathways are characterised by their high complexity. Mathematical models describing these processes might be of great help to gain qualitative and, most importantly, quantitative knowledge about such complex systems. However, a detailed mathematical description of these systems leads to nearly unmanageably large models, especially when combining models of different signalling pathways to study cross-talk phenomena. Therefore, simplification of models becomes very important. Different methods are available for model reduction of biological models. Importantly, most of the common model reduction methods cannot be applied to cellular signal transduction pathways. Using as an example the epidermal growth factor (EGF) signalling pathway, we discuss how quantitative methods like system analysis and simulation studies can help to suitably reduce models and additionally give new insights into the signal transmission and processing of the cell. [less ▲]

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See detailTowards whole cell "in silico" models for cellular systems: model set-up and model validation
Kremling, A.; Bettenbrock, K.; Fischer, S. et al

in Lecture Notes in Control and Information Sciences: Proceedings of the first multidisciplinary international symposium on Positive Systems (2004)

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See detailAn approach for dividing models of biological reaction networks into functional units
Ederer, M.; Sauter, Thomas UL; Bullinger, E. et al

in Simulation (2003), 79

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See detailBiosystems Engineering: Applying methods from systems theory to biological systems
Kremling, A.; Sauter, Thomas UL; Bullinger, E. et al

in Proceedings of the 2nd International Conference on Systems Biology 4.-7.11.2001, Pasadena (2001)

Detailed reference viewed: 65 (0 UL)