Professorship for Computational Molecular Medicine


The working group's research activities concentrate on three main areas:

Development of statistical methods: Development and evaluation of complex biostatistical methods, with a focus on prediction modeling, prediction error estimation, variable selection, parameter tuning, high-dimensional data, machine learning methods such as random forest

Statistical applications/consulting: Applications of statistical methods to biomedical data, in particular - but not limited to - high-throughput molecular ("omics") data

Epistemology: "Research on (applied statistical) research" focusing on the concept of "evidence" in methodological statistical research, the design of reliable comparison studies and good practice issues related to fishing for significance and researchers' degrees of freedom