Over recent years, we have witnessed tremendous progress in genomic technologies. As a result we are now in a position to sequence large numbers of genomes from a variety of organisms in no time and at reasonable cost. However, genomic data in itself does little more than clogging up computers. 

In order to extract meaningful biological information from genomic data, we need dedicated methodological tools. This is where we fit in and our mission statement is to harness genomic information by developing, refining and applying computational tools to genomic datasets to address important and interesting scientific questions.

Our core interest is to use genomic data to reconstruct past population history of a variety of organisms. One research focus in the lab is on the reconstruction of human colonisation of the world. One key motivation behind this work is to generate “null models” for the current distribution of genetic diversity, which allow controlling for the effect of past demography when making inference on genes that may have been affected by natural selection.

We also work on the reconstruction of infectious disease outbreaks and epidemics on a series of human (MRSA, the plague, malaria, influenza) and wildlife pathogens (Batrachochytrium dendrobatidis, ranavirus). The focus of this work is increasingly on why some lineages have been more successful than others. In this context, one aspect we are increasingly getting interested in is the prediction of drug resistance and their associated fitness costs from genome sequence data.

Our work spans a large spectrum ranging from the fundamental (e.g. reconstructing historical plague pandemics) to the applied (e.g. tracking MRSA infections in hospital wards). Indeed, we do not feel there must be a divide between fundamental and applied science, and while our research is primarily driven by scientific curiosity, we aim at contributing with our work to the genomic revolution in medicine, public health and conservation biology.