AICES - Data driven modelling in computational engineering sciences


Head of the Institute

Univ.-Prof. Dr. rer. nat. Andreas Schuppert

Field of Study

CES, Biomedical Engineering, Biotechnology

Main Focus

Hybrid modelling, Systems biomedicine, Bioinformatics

Research Focus

Researvch activities are focussed on data driven modelling of complex systems. The applications span a wide area from chemical and biotechnological process analysis and -modelling up to gene diagnostics in oncology and cellular reengineering in stem cell technology. The joint scientific backbone is the application of inverse problem methods on the high-dimensional data spaces arising in biological applications, such as micro-array gene- or protein expressions analysis or next generation sequencing.

In detail:

  • Hybrid modeling of complex systems with functional networks Reengineering of functional network structures from data, with applications in unravelling of mechanisms of drug action.
  • Modeling of regulation structures of biological systems by integration of statistical thermodynamics approaches, data mining and hybrid models, with applications in cellular reengineering.
  • Data driven modeling of clinical parameters from –omics data with applications in gene diagnostics, e.g. in oncology.


AICES - Data driven modelling in computational engineering scienceAugustinerbach 2a

Phone: +49 241 80-991 44 or 99202
Fax: +49 241 80-628498

Homepage AICES