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