Our group consists of scientists with mathematics and statistics background. We develop and apply probabilistic models and statistical methods for the analysis of biological data. The employed models range from differential equation (ODE, SDE, PDE) models to stochastic mixture models. Inference tools include classical estimation and test theory, regularised regression, Bayesian parameter estimation, machine learning and functional data analysis.

Our emphasis is on biological and medical applications, for example environmental health risks and genomic, transcriptomic and phenomic data analysis. We are working in close connection to other research teams of the Institute of Computational Biology. In addition, we offer support for statistical data exploration via the Core Facility Statistical Consulting.

We are closely linked to the Data Science group at the Faculty of Business Administration and Economics at Bielefeld University. Please visit the Data Science group's web page for information about our activities in Bielefeld.

source: HMGU