Gaining details of the demographic history of a population of organisms, in particular humans, is quite a complex and beneficial field of research. Beside a lot of different information, genetic data are especially useful for such kind of analyses, since many processes and circumstances shape the genome of individuals over time. These traces can then be used to derive details about the history of a population. There exist a lot of different methods to analyze genetic data which are drawn in the present, and to make statements about the foretime.

I am particularly interested in developing new approaches to infer the demographic history from genome-wide Single Nucleotide Polymorphism (“SNP”) data and thereby investigating the effects of ascertainment bias. Furthermore, computational methods such as Approximate Bayesian Computation and MCMC play a decisive role in my research.

Another important part of my work is the study of the effects of different processes like mutation, natural selection, genetic drift, and recombination and how they shape the genome.

Contact:

Christoph Theunert: christoph_theunerteva.mpg.de