- computer simulation of virtual infection models with Candida albicans
- population-based, state-based and agent-based modelling of immune responses to C. albicans
- estimation of a priori unknown model parameter using global optimization algorithms
|since 2016||Postdoctoral researcher in the group Applied Systems Biology at Hans Knöll Institute|
|2017||PhD in Bioinformatics at the Friedrich Schiller University Jena|
|2011||Diploma in Bioinformatics at the Friedrich Schiller University Jena|
(2018) Predictive virtual infection modeling of fungal immune evasion in human whole blood. Frontiers in Immunology [Accepted]
(2017) Dimensionality of motion and binding valency govern receptor-ligand kinetics as revealed by agent-based modeling. Frontiers in Immunology 8, 1692.
(2015) Neutrophil activation by Candida glabrata but not Candida albicans promotes fungal uptake by monocytes. Cell Microbiol 17(9), 1259-1276.
(2015) A second stimulus required for enhanced antifungal activity of human neutrophils in blood is provided by anaphylatoxin C5a. The Journal of Immunology 194(3), 1199-1210.
(2015) Bottom-up modeling approach for the quantitative estimation of parameters in pathogen-host interactions. Frontiers in Microbiology 6(608), *authors contributed equally.
(2014) A virtual infection model quantifies innate effector mechanisms and Candida albicans immune escape in human blood. PLoS Comput Biol 10(2), e1003479, */⁺authors contributed equally.
(2014) Epithelial invasion outcompetes hypha development during Candida albicans infection as revealed by an image-based systems biology approach. Cytometry A 85(2), 126-139.