Complex Systems


Approaching biological systems in a holistic way implies to acknowledge living systems within their natural complexity. In contrast to reductionist approaches, methods for complex systems have to cope with the difficulty to not being able to deal with assumptions reducing the system to a small size model. Combining theoretical work from the field of systems theory, mathematics and machine learning, our research aims at providing tools to analyse and model complex systems in a holistic way based on experimental data.
The overall aim of our research is to unravel generic characteristics of complex biological systems. In order to identify such principles, systems have to be analysed and studied on various scales and in various scenarios. 

Current examples for fields of applications are

  • gut microbiome analysis in the context of diabetes research
  • lung microbiome analysis in the context of COPD research
  • networks of plant-microorganism interactions

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