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Generalized additive models (GAM) for modelling nonlinear effects of continuous covariates are now well established tools for the applied statistician. In this paper we develop Bayesian GAM's and extensions to generalized structured additive regression based on one or two dimensional P-splines as the main building block. The approach extends previous work(More)
To identify epigenetic patterns, which may predispose to type 2 diabetes (T2D) due to a family history (FH) of the disease, we analyzed DNA methylation genome-wide in skeletal muscle from individuals with (FH(+)) or without (FH(-)) an FH of T2D. We found differential DNA methylation of genes in biological pathways including mitogen-activated protein kinase(More)
Two-photon microscopy in combination with novel fluorescent labeling techniques enables imaging of three-dimensional neuronal morphologies in intact brain tissue. In principle it is now possible to automatically reconstruct the dendritic branching patterns of neurons from 3-D fluorescence image stacks. In practice however, the signal-to-noise ratio can be(More)
The three-dimensional (3D) structure of neural circuits represents an essential constraint for information flow in the brain. Methods to directly monitor streams of excitation, at subcellular and millisecond resolution, are at present lacking. Here, we describe a pipeline of tools that allow investigating information flow by simulating electrical signals(More)
Using a literature review of 80 journals and proceedings we identified 23 research papers discussing driver, challenges and consequences of e-recruiting. In total 14 drivers, 15 challenges and 9 consequences of implementing and using e-recruiting has been identified. Based on these results the paper introduces a model of drivers, challenges and consequences(More)
Models with structured additive predictor provide a very broad and rich framework for complex regression modeling. They can deal simultaneously with nonlinear co-variate effects and time trends, unit-or cluster-specific het-erogeneity, spatial heterogeneity and complex interactions between covariates of different type. In this paper, we propose a(More)
In this paper we discuss the implementation of parallel multigrid methods on unstructured locally refined meshes for 2D linear elasticity calculations. The problem of rebalancing the workload of the processors during execution of the program is discussed in detail and a load balancing algorithm suited for hierarchical meshes is proposed. For large problems(More)