since 1989: alive
1993-1996: Kindergarten (Specialization in indoor sand logistics and plastic toy melting)
2009: Abitur (at Gymnasium Alexandrinum Coburg)
- Molecular systems biology, i.e. the integration of the biological parts list (single molecules and their biochemical properties and functions) into coherent and preferably quantitative models of biological "systems", hopefully capturing the relevant molecular interactions and processes in order to be able to reproduce/explain or predict the emergent properties in a given biological situation. Of course this is only my personal definition of systems biology and there are many more.
- Multi-omics (another buzzword and a subfield of Molecular Systems Biology, sometimes also referred to as Poly-omics, Inter-omics, Ultra-omics or Hyper-omics): the statistical and model-based joint analysis of genome-wide measurements (preferably on the same samples) of relevant biomolecular entities (transcriptome, proteome, metabolome, etc.) with the ultimate aim of figuring out "what is going on" in a biological system.
- High-dimensional statistics and Machine Learning: methods meant to deal with the situation that the dimension (for example, the number of genes) in a data analysis problem exceeds or is comparable to the number of samples. This is in contrast to a lot of classical statistical theory and applications but highly relevant for many modern day applications (systems biology being one of them). This situation in conjunction with the need for computationally efficient implementations of such methods (a problem I am also very interested in) could be called Big Data (especially if this were a grant proposal).
From deterministic Boolean networks to stochastic continuous models.
Technical University Munich & Institute of Computational Biology (Helmholtz Centre Munich), 2014
Biostatistics Research Group
- Summer 2014: Tutor for "Practical Course Genetics"
Genetics Department, Technical University Munich