TIMed CENTER Center for Technological Innovation in Medicine
Target: Development of self-learning search algorithms for high-resolution mass spectra.
Usually, mass spectrometry is used to identify proteins in biological samples. In the interdisciplinary bioinformatics-project SESAM, a research group at the faculty in Hagenberg develops a series of new idenfication algorithms. These algorithms are specifically designed for the analysis of such mass spectra and respect various information sources.
The first research results give an understanding of the wide range of opportunities: One project about the analysis of mass spectra has been completed already. An innovative scoring-function that was developed by the research group bioinformatics of the University of Applied Sciences Upper Austria at the campus Hagenberg in cooperaton with the research group for proteomics of the IMP in Vienna provides remarkable identification rates. These are not only similar to the ones of Mascot, the current standard method in the identification of mass spectra, but sometimes even higher.
All results that are about to be drawn from this research projects are intended to be made available to both the bioinformatics- and proteomics-community. It is expected that the identification rates of peptides in general as well as of unknown modifications in particular, which are about to be improved by means of informatics, will grant a better insight into the proteome.
- Head: FH-Prof. PD DI Dr. Stephan Winkler
- Funding Program: FWF (Translational Research)
- Duration: seit 03/2013
- Faculty: Hagenberg
Please find a selection of papers published about this project by clicking on the following link.