Computational Quantitative Proteomics

The working group Computational Quantitative Proteomics is coordinated by Dr. Michael Turewicz. We focus on the analysis of expression of biological quantities that have been measured in multiple samples (expression profiles) using high-throughput omics technologies such as quantitative proteomics. By the analysis of medically relevant data such as expression data, clinical data and mass spectra, for instance, we are able to discover biomarker candidates. Moreover, we focus on the analysis of biomedical texts using text mining methods. Within the working group, we develop, investigate and apply methods and algorithms in the following research areas:

  • Discovery of biomarker candidates using machine learning methods
  • Inference and analysis of co-expression networks
  • Biomedical text mining (esp. for our biomarker database BIONDA)
  • Analysis of mass spectra using machine learning methods
  • Statistical analysis of expression data and clinical data (descriptive und differential statistical analysis, study design and sample size estimation, survival analysis)

For these research areas, we provide self-developed and free software tools (e.g., PAA, BIONDA) and workflows as well as consulting and support for bioinformatical and statistical analyses for our cooperation partners in scientific projects.

Working Group Leader

Dr. Michael Turewicz


Ruhr-Universität Bochum
ProDi, Raum E2.260
Gesundheitscampus 4
D-44801 Bochum

Phone: +49 234 32 18107