07 Fakultät Konstruktions-, Produktions- und Fahrzeugtechnik
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/8
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Item Open Access Indefinite linear quadratic optimal control: periodic dissipativity and turnpike properties(2018) Berberich, JulianItem Open Access Understanding the mechanisms of robustness in intracellular protein signalling cascades and gene expression(2018) Paul, Debdas; Radde, Nicole (Prof. Dr. rer. nat.)We seek to understand the structural as well as the mechanistic basis of robustness in intracellular protein signalling cascades and in transcriptional regulation of gene expression. For protein signalling cascades, we employ a comparison based study involving a single, a double and a cascade of two double phosphorylation-dephosphorylation (PD) cycles. Using deterministic modelling approaches based on ordinary differential equations (ODE), we observe that the cascade of two double PD cycles exhibits robust output behaviour compared to that of a single and a double PD cycle upon constant as well as time- varying input perturbations. Furthermore, a system theoretic analysis reveals that the protein phosphorylation cascades act as an efficient low-pass filter that attenuates the noise mimicked as high-frequency input signals. Afterwards, we extend the study for a stochastic environment. Simulation results based on the stochastic simulation algorithm (SSA) reveal a novel phenomenon called dynamic sequestration that plays an ambivalent role as an intrinsic noise filter. Overall, the analysis indicates that complexity can be one of the basic principles of robust biological designs such as intracellular protein signalling cascades. A major function of intracellular signalling cascades is to transmit the extracellular signal to the nucleus to initiate the process of gene expression. Gene expression is an intrinsically stochastic process that results into cell-to-cell variability in protein and messenger RNA (mRNA) levels, often termed as the expression noise. In spite of such noise, how cells achieve robustness is therefore a fundamental biological problem. We conclude the thesis by introducing a rule-based modelling approach based on the Kappa (κ) platform with the goal to understand the underlying mechanisms that ensure robust cellular functioning during gene expression. In particular, we introduce a gene expression model that keeps the process of transcription and excludes the process of translation. Therefore, we quantify the expression noise using mRNA which is the end product of transcription. Besides, the motivation behind adopting a rule-based modelling approach is that unlike the ODE-based approach, the former subsumes the combinatorial complexity arises due to various binding configurations of transcription factors (TF) for regulation of gene expression and offers a compact graphical representation of the same. Afterwards, the representation is transformed into an equivalent set of executable κ rules that are simulated using the SSA to obtain distributions of mRNA copy numbers corresponding to different regulatory mechanisms.Item Open Access Modeling of biocatalytic reactions: a workflow for model calibration, selection, and validation using Bayesian statistics(2019) Eisenkolb, Ina; Jensch, Antje; Eisenkolb, Kerstin; Kramer, Andrei; Buchholz, Patrick C. F.; Pleiss, Jürgen; Spiess, Antje; Radde, NicoleWe present a workflow for kinetic modeling of biocatalytic reactions which combines methods from Bayesian learning and uncertainty quantification for model calibration, model selection, evaluation, and model reduction in a consistent statistical frame-work. Our workflow is particularly tailored to sparse data settings in which a considerable variability of the parameters remains after the models have been adapted to available data, a ubiquitous problem in many real-world applications. Our workflow is exemplified on an enzyme-catalyzed two-substrate reaction mechanism describing the symmetric carboligation of 3,5-dimethoxy-benzaldehyde to (R)-3,3',5,5'-tetramethoxybenzoin catalyzed by benzaldehyde lyase from Pseudomonas fluorescens. Results indicate a substrate-dependent inactivation of enzyme, which is in accordance with other recent studies.Item Open Access Multivariable controller design for an industrial distillation column(1992) Allgöwer, Frank; Raisch, JörgIn this paper, we report our experience with the design of linear multivariable controllers for a staged binary distillation column with 40 trays. Controller design methods include H∞-minimization, DNA-design, CL-design and H2minimization. Results obtained at the real plant are shown.Item Open Access A systems science view on cell death signalling(2007) Eißing, Thomas; Allgöwer, Frank (Prof. Dr.-Ing.)This thesis provides new insight into cellular signal transduction by integrating biological knowledge into mathematical models, which are subsequently analysed using systems theoretic methods. Signal transduction has been dissected using molecular and genomic approaches providing exciting insight into the biochemistry of life. However, a detailed understanding of its dynamic properties remains elusive. The application of systems science ideas to biology is promising to put the pieces of molecular information back together, as important properties of life arise at the system level only. For example, certain signalling pathways convert graded input signals into all-or-none output signals constituting biological switches. These are implicated in cellular memory and decisions. One such decision is whether or not to undergo programmed cell death (apoptosis). Apoptosis is an important physiological process crucially involved in the development and homoeostasis of multicellular organisms. Switches, such as in apoptosis, can be represented by ordinary differential equation models showing bistable behaviour. Different biochemical mechanisms generating bistability in reaction schemes as encountered in apoptosis are presented and compared in this thesis. Bifurcation studies reveal structural and parametric requirements for bistability. In combination with reported kinetic information, inconsistencies in the literature view of apoptosis signalling in humans are revealed. An additional regulatory mechanism is proposed, which is now supported by experimental evidence. Extended robustness analyses indicate that the cell has achieved a favourable robustness-performance trade-off, imposed by network structure and evolutionary constraints. On the one hand, inhibitors of apoptosis function as noise filters and reduce variability caused by the stochastic nature of reactions. Further, qualitative properties such as bistability are comparably robust to parameter changes supporting proper decisions. On the other hand, quantitative aspects are comparably sensitive. This allows for variability in a population, as observed in experiments, and which is likely important for physiological function as recently indicated in immunological studies. The analyses further indicate that the trade-off leads to fragilities. For example, an up-regulation of inhibitors of apoptosis, as observed in certain cancers, can not only desensitise cells to apoptotic stimuli, as also suggested by experimental studies, but can contribute to cancer aggressiveness and progression through additional mechanisms. Thereby, the analyses provide insight of pharmaceutical relevance. Several results presented in this thesis are not restricted to apoptosis signalling only, but are conceptually relevant to various other signal transduction pathways.Item Open Access The physics behind systems biology(2016) Radde, Nicole; Hütt, Marc-ThorstenSystems Biology is a young and rapidly evolving research field, which combines experimental techniques and mathematical modeling in order to achieve a mechanistic understanding of processes underlying the regulation and evolution of living systems. Systems Biology is often associated with an Engineering approach: The purpose is to formulate a data-rich, detailed simulation model that allows to perform numerical (‘in silico’) experiments and then draw conclusions about the biological system. While methods from Engineering may be an appropriate approach to extending the scope of biological investigations to experimentally inaccessible realms and to supporting data-rich experimental work, it may not be the best strategy in a search for design principles of biological systems and the fundamental laws underlying Biology. Physics has a long tradition of characterizing and understanding emergent collective behaviors in systems of interacting units and searching for universal laws. Therefore, it is natural that many concepts used in Systems Biology have their roots in Physics. With an emphasis on Theoretical Physics, we will here review the ‘Physics core’ of Systems Biology, show how some success stories in Systems Biology can be traced back to concepts developed in Physics, and discuss how Systems Biology can further benefit from ist Theoretical Physics foundation.Item Open Access Mathematical modeling of the pituitary-thyroid feedback loop: role of a TSH-T3-shunt and sensitivity analysis(2018) Berberich, Julian; Dietrich, Johannes W.; Hoermann, Rudolf; Müller, Matthias A.Despite significant progress in assay technology, diagnosis of functional thyroid disorders may still be a challenge, as illustrated by the vague upper limit of the reference range for serum thyrotropin (TSH). Diagnostical problems also apply to subjects affected by syndrome T, i.e. those 10% of hypothyroid patients who continue to suffer from poor quality of life despite normal TSH concentrations under substitution therapy with levothyroxine (L-T4 ). In this paper, we extend a mathematical model of the pituitary-thyroid feedback loop in order to improve the understanding of thyroid hormone homeostasis. In particular, we incorporate a TSH-T3 –shunt inside the thyroid, whose existence has recently been demonstrated in several clinical studies. The resulting extended model shows good accordance with various clinical observations, such as a circadian rhythm in free peripheral triiodothyronine (FT3). Furthermore, we perform a sensitivity analysis of the derived model, revealing the dependence of TSH and hormone concentrations on different system parameters. The results have implications for clinical interpretation of thyroid tests, e.g. in the differential diagnosis of subclinical hypothyroidism.Item Open Access Sampling-based Bayesian approaches reveal the importance of quasi-bistable behavior in cellular decision processes on the example of the MAPK signaling pathway in PC-12 cell lines(2017) Jensch, Antje; Thomaseth, Caterina; Radde, NicolePositive and negative feedback loops are ubiquitous motifs in biochemical signaling pathways. The mitogen-activated protein kinase (MAPK) pathway module is part of many distinct signaling networks and comprises several of these motifs, whose functioning depends on the cell line at hand and on the particular context. The maintainance of specificity of the response of the MAPK module to distinct stimuli has become a key paradigm especially in PC-12 cells, where the same module leads to different cell fates, depending on the stimulating growth factor. This cell fate is regulated by differences in the ERK (MAPK) activation profile, which shows a transient response upon stimulation with EGF, while the response is sustained in case of NGF. This behavior was explained by different effective network topologies. It is widely believed that this sustained response requires a bistable system. In this study we present a sampling-based Bayesian model analysis on a dataset, in which PC-12 cells have been stimulated with different growth factors. This is combined with novel analysis methods to investigate the role of feedback interconnections to shape ERK response. Results strongly suggest that, besides bistability, an additional effect called quasi-bistability can contribute to explain the observed responses of the system to different stimuli. Quasi-bistability is the ability of a monostable system to maintain two distinct states over a long time period upon a transient signal, which is also related to positive feedback, but cannot be detected by standard steady state analysis methods.Item Open Access Identifiability and sensitivity analysis of heterogeneous cell population models(2013) Zeng, ShenIn this thesis, we introduce novel concepts to the modeling and analysis of heterogeneous cell populations. Heterogeneous cell populations can be interpreted as large populations of structurally identical cells with heterogeneous parameters and initial conditions. They appear in biological systems such as tissues of higher organisms or colonies of microorganisms. A well-known approach for the modeling of heterogeneous cell populations is the so called density-based approach, in which the state of a heterogeneous cell population is given by the probability density of the cell states. The evolution of the probability densities is in this approach given in terms of a partial differential equation. We extend this approach via a measure theoretical consideration, which exploits the probabilistic nature of the problem. The result of this novel ansatz is a framework in which the evolution of densities is described by operators. One of the key tasks in the analysis of heterogeneous cell population models is parameter estimation. For heterogeneous cell populations we want to estimate the probability density of parameters and initial conditions. However, to be able to perform parameter estimation, one always needs specific identifiability properties of a system. We formulate for the first time the concept of structural identifiability of a heterogeneous cell population model. It is revealed that this concept is closely related to observability of the corresponding single cell model. The connection between both concepts is studied and illuminated in a concrete example. The second emphasis of this thesis is the implementation of sensitivity analysis to the class of heterogeneous cell population models. Here we study sensitivity with respect to variations or misspecifications in the probability density of parameters and initial conditions.Item Open Access Moment dynamics of Zirconia particle formation for optimizing particle size distribution(2019) Halter, Wolfgang; Eisele, Rahel; Rothenstein, Dirk; Bill, Joachim; Allgöwer, Frank