Applied Bioinformatics Group


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Computational Mass Spectrometry

High-throughput analysis of proteins and proteomes plays an important role in biomedical research and development. Our group develops novel algorithms for the analysis of high-throughput proteomics and metabolomics data. We work in close collaboration with several leading groups world-wide to apply these methods to problems in cancer research, immunology, and stem cell research.

Proteomics

Our current efforts in proteomics are focused on efficient algorithms for labeled and label-free quantification, novel identification methods (consensus identification, de novo methods) and data integration and processing. We contribute to the PSI community standards (mzML, mzIdentML, traML) in order to facilitate data exchange in mass spectrometry. The algorithms and tools developed in this context are all available as open source in the OpenMS project. We also employ these methods in numerous collaborations with experimental partners world-wide to study a wide range of biomedical problems.

Metabolomics

In metabolomics, we develop novel methods for metabolite identification and quantification. Such methods play an important role in the discovery of novel biomarkers for different diseases, e.g. type 2 diabetes mellitus. The identification of unknown metabolites poses a challenge, because metabolite databases cover only a small portion of the human metabolome. For this reason, further efforts are put into the annotation of unknown metabolites from different human body tissues and fluids, extending the knowledge of metabolite databases.

Software for Computational Mass Spectrometry

OpenMS is an open source C++ library for LC/MS data management, reduction, evaluation, visualisation, storage and sophisticated statistical analyses. It is intended as a tool for rapid prototyping of novel algorithms in computational mass spectrometry. TOPP - The OpenMS Proteomics Pipeline is a set of applications based on OpenMS that demonstrate the power and flexibility of the framework. More details on OpenMS and TOPP can be found on the OpenMS homepage. The OpenMS proteomics pipeline is currently used in a number of projects, among them the systems biology project SARA. In order to process and analyze proteomics data in a high-throughput setting, we are also involved in parallel computing and Grid Computing.

 

People working in this area

Johannes Junker, Erhan Kenar, Sven Nahnsen, Marc Rurik, Timo Sachsenberg, Mathias Walzer

 

 

Selected publications