The development of statistical methods geared towards applications in medicine, agriculture and the life sciences has a long standing tradition. Famous names in the field such as Galton, Fisher, and Cox are connected to classical methodology such as regression, ANOVA and survival, analysis. The current rapid technological progress permits for the sequencing of DNA and RNA at a large scale even at a single cell resolution, producing huge amounts of data. Their analysis leads to new statistical challenges. Recent developments in the area of high dimensional inference, large scale multiple testing, and hierarchical models have been inspired by the demands that arose with the analysis of such data. Potential applications range from personalized medicine to a better understanding of the underlying mechanisms of evolution. Methods for analyzing large scale genomic data are developed by the members of the institute participating in this research field. As also the effect of climate change is one of our topics, this project fits into the university-wide research initiative Sustainable Development: Responsible Technologies & Management.