Computional Proteomics

Proteomics is a relatively young discipline dealing with the complicated protein mixture in biological systems, for example the human body. Changes in the concentration of some protein species can often be directly linked to  diseases, such as cancer. In this project we develop algorithms capable of identifying changes in the very high dimensional proteome data we are getting from clinical partners. In particular, we are interested in tiny signals that are usually hidden in the noisy part of the data and not detectable by current approaches. Nevertheless, these very small signals are crucial for reliable classification of biological samples.


Detected diseases-specific fingerprints are further analyzed for identifying their molecular causes. We are mainly interested in the kinetic changes inside the system that lead to the observed changes in protein concentration; changes kinetics are often caused by changes in the underlying proteases activity.


For all our methods we put special emphasis on the applicability in clinical areas, i.e., the algorithms are designed to be simple, fast and reliable, with particular respect to sensitivity and specificity sufficient for clinical requirements.


For further details please "click here".


Tim Conrad


Group Members:

Tim Conrad, Axel Rack, Stephan Aiche,

Pooja Gupta, Sandro Andreotti, Sharon Bruckner, Iliusi Vega, Christof Schuette

Selected Publication

  • Conrad, T. O. F. (2008) New Statistical Algorithms for the Analysis of Mass Spectrometry Time-Of-Flight Mass Data with Applications in Clinical Diagnostics. PhD thesis, Freie Universität Berlin.

  • Stenziok, R. and Hinz, S. and Wolf, C. and Conrad, T. O. F. and Krause, H. and Lingnau, A. and Lein, M. and Schostak, M. and Miller, K. and Schrader, M. (2009) Serum proteomic profiling by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry in testicular germ cell cancer patients. World J of Urology.


  • Fiedler, G. M. and Leichtle, A. and Kase, J. and Baumann, S. and Ceglarek, U. and Felix, K. and Conrad, T. O. F. and Witzigmann, H. and Weimann, A. and Schütte, Ch. and Hauss, J. and Büchler, M. and Thiery, J. (2009) Serum Peptidome Profiling Revealed Platelet Factor 4 as a Potential Discriminating Peptide Associated With Pancreatic Cancer. Clinical Cancer Research, 15 (11). pp. 3812-3819. ISSN 1078-0432



  • Universitätsklinikum Leipzig
  • Universitätsklinikum Charité
  • Microsoft Research
  • IBM Deutschland