Algorithmic Proteomics

The working group (WG) ‚Algorithmic Proteomics‘ is coordinated by Dr. Michael Kohl. Focus areas of the working group are the following topics:

  • Flexible and comprehensively scalable protein inference approaches based on peptide identifications obtained from different MS/MS analysis algorithms (‘search engines’)
  • Development of technology specific algorithms (e.g. decoy approaches specific for spectra or techniques for the detection of protein variants)
  • Label free and label based quantification of MS data.
  • Analysis of targeted Proteomics data sets (Selected/Multiple Reaction Monitoring (SRM/MRM))
  • Spatial Proteomics (cross-linking)
  • The working group is involved in the development of standards for description and storage of Proteomics data (HUPO-PSI: Proteomics Standards Initiative (PSI) of the Human Proteome Organization (HUPO))
  • Combined analysis of data obtained from different high – throughput techniques (mult-Omics data processing)

Current research activities of the working group include

  • the integration of additional data types for multi-Omics analysis,
  • the development of a peptide based approach for the comparison of data obtained from Proteomics experiments
  • the development of mathematical models that mimic the dynamics of protein networks within a cell and
  • the advancement of machine learning algorithms that are specifically tailored for classification of biomedical Proteomics data (e.g. techniques for application in case of small sample sizes).

We implement several software tools (e.g. CalibraCurve and PIA) and different software workflows that are made available to the Proteomics community free of charge.