Theoretical Evolution group
Biological networks contain multiple components that interact with each other in many different ways. Often the functionality of these networks depends on the ability of molecules to interact specifically with certain targets, while simultaneously avoiding interaction with many other potential targets. Given the low interaction energies and large number of molecular species, this raises fundamental theoretical questions concerning the evolution of such networks.
We are a theoretical-computational group. We use a variety of physical and mathematical approaches, in particular population genetics models, stochastic simulations and genomic data analysis.
Current projects in the lab are:
Evolution of “self-incompatibility” proteins: “Self-incompatibility” is a general name for molecular mechanisms, plants have developed to avoid self-fertilization, which might lead to the spread of deleterious mutations. As a medium-sized network with strong selection on the interactions, self-incompatibility is an excellent model system for network evolution. Self-incompatibility forms barriers to reproduction of many agricultural crops. A better understanding of this mechanism is an essential step in designing efficient breeding strategies. To read more…
Evolution on high-dimensional fitness landscapes: evolutionary dynamics is often described as a trajectory on a mountainous “landscape”, where each position represents a particular genotype and its height represents the reproductive success (fitness) of that genotype. Analysis of evolutionary dynamics on such landscapes is hard, because genotypes are high-dimensional and the landscape is often rugged and has multiple maxima. we develop theoretical tools to study evolution in this setup. To read more…
We are also interested in general evolutionary theory questions. For more details on current and previous projects check out our research page.