Project: Modelling the antibody and B cell response to vaccination and infection
Although it is known that an individual’s infection history has a large impact on the response to subsequent infections and vaccinations, the underlying mechanisms remain to be described. Immunological memory, consisting of pre-existing long lived plasma cells and memory B cells, contains important biological information, the understanding of which would be a major step towards optimised vaccine design. My research employs stochastic modelling to contribute to that.
The ABcDModel (Antibody and B cell Dynamic Model) is an extension of a previously published computational model which simulates realistically sized B cell repertoires by representing single molecules in shape space. It allows us to study the effect of changes in central processes of B cell responses, such as activation, affinity maturation and competition of naive and memory B cells, to infection outcome.
In collaboration with Dr. Frederik Graw’s Modelling Infection and Immunity group, we use Bayesian approaches to fit the model to experimental data. Eventually, we aim to use the ABcDModel to evaluate vaccination scenarios based on prior immunity and as such contribute to increasing protection provided by vaccines.
Education
MSc Molecular Biosciences, major Systems Biology at Heidelberg University (Oct 2018 – Mar 2021)
BSc Molecular Biosciences at Salzburg University and Linz University (Oct 2014 – Jul 2017)
Contact Information
Email: antonia.netzl[at]bioquant.uni-heidelberg.de