Tel.: +41 (44) 634 46 47
I am at the Division of Biostatistics since April 2007.
Currently, I am working on a research project, funded by the the "Forschungskredit" of the University of Zurich, to develop Bayesian methods for genome-scale count data obtained by high-throughput
experiments. The goal is to incorporate the inherent dependence along the genome to improve statistial approaches, for example for the interrogation of methylation states. For more details, see the project summary. Furthermore, I work part time as a postdoc in the statistical genomics group of Mark D. Robinson.
In October 2010, I obtained the doctoral degree in Statistics from the Faculty of Science at the University of Zurich. My dissertation entitled
Multivariate Age-Period-Cohort Models
aims at extending univariate age-period-cohort models to allow for data stratified according to additional criteria, for example sex or nationality. Three different approaches to the analysis of multivariate age-period-cohort models are presented. The methods involved in the thesis include efficient Markov chain Monte Carlo (MCMC) techniques, based on auxiliary mixture sampling and a Metropolis-Hastings algorithm, and integrated nested Laplace approximations (INLAs), which provide a deterministic alternative to MCMC simulations.
After obtaining my PhD I extended Gaussian Markov random field models to realistically describe dependence in large observational databases based on a Kronecker product precision matrix. Full Bayesian inference was mainly performed using INLA.
Before moving to Zurich I graduated in Bioinformatics from LMU/TU Munich. In my Master's Thesis I developed Bayesian methods for detecting selection in the genome. In my Bachelor's Thesis I worked on the empirical comparison of statistical methods for outbreak detection in surveillance data and contributed to the development and implementation of the R-package surveillance. You can find my theses here:
CV and a list of publications and talks:
Riebler A., Held L. and Stephan W. (2008). Bayesian variable selection for detecting adaptive genomic differences among populations, Genetics, 178(3): 1817-1829.