Efficient multiple testing for large structured problems

Modern day technology allows us to collect and store more data than ever before. Although the abundance of data offers great opportunities with respect to formulating and testing all kinds of hypotheses and with respect to discovering and modeling patterns that can be used for future prediction, these opportunities do not come without risks. If the data is explored in a too naive manner, there is a very large probability that, at least part of, the actual findings will not be reproducible in future research. When the number of hypotheses or the number of parameters within a model increases, the possibility of actually ending up in such a situation increases as well. Profiting from all available data, while preventing chance findings from occurring, will call for advanced statistical techniques. The development of such techniques is the subject of this thesis. We focus both on multiple hypothesis testing and on the construction of prediction models. Throughout the thesis, emphasis is placed on the development of methods that are efficient, both from a power perspective and from the perspective of computational feasibility.UBL - phd migration 201

Computational modeling of Adelta-fiber-mediated nociceptive detection of electrocutaneous stimulation

Sensitization is an example of malfunctioning of the nociceptive pathway in either the peripheral or central nervous system. Using quantitative sensory testing, one can only infer sensitization, but not determine the defective subsystem. The states of the subsystems may be characterized using computational modeling together with experimental data. Here, we develop a neurophysiologically plausible model replicating experimental observations from a psychophysical human subject study. We study the effects of single temporal stimulus parameters on detection thresholds corresponding to a 0.5 detection probability. To model peripheral activation and central processing, we adapt a stochastic drift-diffusion model and a probabilistic hazard model to our experimental setting without reaction times. We retain six lumped parameters in both models characterizing peripheral and central mechanisms. Both models have similar psychophysical functions, but the hazard model is computationally more efficient. The model-based effects of temporal stimulus parameters on detection thresholds are consistent with those from human subject data

Quest for a Nuclear Georeactor

Knowledge about the interior of our planet is mainly based on the interpretation of seismic data from earthquakes and nuclear explosions, and of composition of meteorites. Additional observations have led to a wide range of hypotheses on the heat flow from the interior to the crust, the abundance of certain noble gases in gasses vented from volcanoes and the possibility of a nuclear georeactor at the centre of the Earth. This paper focuses on a proposal for an underground laboratory to further develop antineutrinos as a tool to map the distribution of radiogenic heat sources, such as the natural radionuclides and the hypothetical nuclear georeactor.Comment: Invited talk presented at the International Symposium on Radiation Physics, Cape Town, 2003. Manuscript is submitted to Radiation Physics and Chemistr

Draft Genome Sequence of Streptococcus thermophilus C106, a Dairy Isolate from an Artisanal Cheese Produced in the Countryside of Ireland

Item does not contain fulltextThe lactic acid bacterium Streptococcus thermophilus is widely used for the fermentation of dairy products. Here, we present the draft genome sequence of S. thermophilus C106 isolated from an artisanal cheese produced in the countryside of Ireland