Evolutionary Systems Biology
Evolutionary and comparative methods are ubiquitous in bioinformatics, as they enable more reliable annotation and prediction of e.g. protein function and protei n structure. At a practical level, we are interested in evolutionary methods in the context of predicting protein interaction, metabolic and signalling networks in biomedically or industrially important microbes and humans.
On a more fundamental level, the current influx of comprehensive, if often not very reliable, biological data allows us to address classical evolutionary questions in new light. We are particularly interested in the dynamics underlying the evolution of networks, and the co-evolution of interacting genes and proteins. To this end, we use a combination of modelling and data-driven analyses which can be combined using suitable statistical and inferential tools that are being developed by the group.
At the moment, relevant data are only available at the species level. In the absence of population level data, we are also studying mathematical and computational evolutionary models of biological systems. This allows us to assess the effects of epistatic interactions, robustness and the evolution of molecular networks more generally in population genetics and dynamics frameworks.