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A mathematical modeling framework to simulate and analyze cell type transitions
The quantitative understanding of changes in cell types, referred to as cell type transitions, is fundamental to advance fields such as stem cell research, immunology, and cancer therapies. This thesis provides a mathematical modeling framework to simulate and analyze cell type transitions. The novel methodological approaches and models presented here address diverse levels which are essential in this context: Gene regulatory network models represent the cell type-determining gene expression dynamics. Here, a novel construction method for gene regulatory network models is introduced, which allows to transfer results from generic low-dimensional to realistic high-dimensional gene regulatory n...
Analysis and Control of Cellular Ensembles. Exploiting dimensionality reduction in single-cell data and models
An ensemble system is a collection of nearly identical dynamical systems which admit a certain degree of heterogeneity, and which are subject to the restriction that they may only be manipulated or observed as a whole. This thesis presents analysis and control methods for cellular ensembles by considering reduced 1-dimensional dynamics of biological processes in high-dimensional single-cell data and models. To be more specific, we address the quest for real-time analysis of biological processes within single-cell data by introducing the measure-preserving map of pseudotime into real-time, in short MAPiT. MAPiT enables the reconstruction of temporal and spatial dynamics from single-cell snaps...
Modeling and Parameter Estimation for Heterogeneous Cell Populations
Most of the modeling performed in biology aims at achieving a quantitative description and understanding of the intracellular signaling pathways within a "typical cell". However, in many biologically important situations even genetically identical cell populations show a heterogeneous response. This means that individual members of the cell population behave differently. Such situations require the study of cell-to-cell variability and the development of models for heterogeneous cell populations. The main contribution of this thesis is the development of unifying modeling frameworks for signal transduction and proliferation processes in heterogeneous cell populations. These modeling framewor...
Stochastic Methods for Parameter Estimation and Design of Experiments in Systems Biology
Markov Chain Monte Carlo (MCMC) methods are sampling based techniques, which use random numbers to approximate deterministic but unknown values. They can be used to obtain expected values, estimate parameters or to simply inspect the properties of a non-standard, high dimensional probability distribution. Bayesian analysis of model parameters provides the mathematical foundation for parameter estimation using such probabilistic sampling. The strengths of these stochastic methods are their robustness and relative simplicity even for nonlinear problems with dozens of parameters as well as a built-in uncertainty analysis. Because Bayesian model analysis necessarily involves the notion of prior ...
The One Behind the Pages
This is an autobiography I completed as part of a project.
Directory Of Plants Containing Secondary Metabolites
Interest in the potential medical use of naturally occuring chemicals in plants is increasing. This is intended to provide a comprehensive and up- to-date directory of plants and the substances found in them. It covers over 8000 plant species. This dictionary, which covers the literature up to the end of 1987, is intended to provide this information in a readily accessible form. Each plant is listed alphabetically according to genus and species. Wherever possible, the original papers have been consulted and references to these are given for each class of compound.
Educating All Children
Experts illuminate the challenges of achieving universal basic and secondary education, discussing the importance and difficulties not only of expanding access to education and but also of improving the quality of education.
