Data-driven research and its applications
The research group is developing and utilizing mathematical and computational methods for data-driven research in computational biology, –medicine and public health
- We develop methods for interpreting complex data from next- and third generation sequencing for understanding the structure & function of non-coding RNA
- We develop methods to infer developmental rules in neurobiology from time-lapse super-resolution microscopy data
- We develop methods for interpretation of (molecular) surveillance data to support public health decision making.
Methods-driven research and its applications
We develop multi-scale numerical methods for pharmacometrics, infection research and public health decision making. In particular, we are currently focusing on:
- Efficient numerical methods for hybdrid stochastic-deterministic simulation of HIV pre-exposure prophylaxis (PrEP)
- Multiscale modelling for heterogeneous data-integration in the context of PrEP
- Efficient stochastic simulation of spreading dynamics on adaptive (contact) networks