AG Fufezan
Schlossplatz 8 48143 Münster
Tel.: +49 251 83-24861
Fax: +49 251 83-28371 Sprechstunde: Mo. 11-12
@ Schlossplatz 8, R105
matched isotope pattern chromatogram
Clustering of protein translation profiles
LC MS/MS alignmet


Research Projects

Computational Biology

Over the last 5 years, we have developed our current computational mass spectrometry software portfolio, which can be used to a) quantify any mass spectrometry data using pyQms, b) analyse very complex samples using our big data infrastructure piqDB, which is optimized for data and project management, c) optimize Proteomics workflows (with respect to LC gradients, identifications and especially quantifications), d) employ automated quality control procedures, e) develop novel visual representations of complex data and f) reduce data complexity with our clustering approach pyGCluster that uniquely takes the uncertainty of the data, i.e. standard deviation, into account.

Overall, a very strong aspect of our research is the ability to develop customized high throughput tools for bioinformatics analysis thanks to our expertise in data mining, big data, distributed computing, biochemical pathway reconstruction and regulatory network discovery. We apply this knowledge to address complex biological questions that employ novel experimental approaches that cannot simply be addressed using standard bioinformatics tools.

Protein turnover and reactive oxygen species

We strive to understand the influence of reactive oxygen species (ROS) and their network on the homeostasis of cells and in particular the defense mechanisms and the quantity and quality of the damage on proteins.

The focus is on photosynthetic organisms since those are intrinsically confronted with elevated levels of basal ROS concentration due to the nature of oxygenic photosynthesis, which trigger the highest protein turnover rates known to man. Using cellular wide approaches, such as proteomics, potential key players in the network are identified employing state of the art bioinformatics. After identifying potential targets, a reverse genetics approach is applied to knock-out or knock-down the appropriate genes of interest and analyse the phenotypes with biophysical techniques, proteomics and bioinformatics / systems biology.

Impressum | © 2010 Institut für Biologie und Biotechnologie der Pflanzen
AG Dr. C. Fufezan
Schlossplatz 8 · 48143 Münster
Tel.: +49 251 83-24790 · Fax: +49 251 83-28371