University of Applied Sciences Upper Austria (FH OOE)
Viktoria Dorfer is Professor for Bioinformatics at FHOOE at the department “Medical- and Bioinformatics” where she teaches proteomics besides algorithm development and programming. Viktoria studied Bioinformatics at the University of Applied Sciences Upper Austria and received her Ph.D. in informatics from the Johannes Kepler University Linz. Her research interests focus on computational proteomics, especially on peptide identification, which was also the topic of her Ph.D. thesis, entitled “Identification of Peptides and Proteins in High-resolution Tandem Mass Spectrometry Data”. Part of her doctoral research was the development of the peptide identification algorithm MS Amanda. At present, Viktoria is leading the computational proteomics subunit of the Bioinformatics Research Group at FHOOE.
Proteins are essential building blocks for every living organism and over the last years, mass spectrometry has become the method of choice for the analysis of those. To understand and investigate cell processes or gain new insights into illnesses triggered by certain proteins or the absence or oversupply of those, the identification and quantification of proteins in the tissue is of primary importance. Since 2011 and in close collaboration with the Mechtler group at the IMP, Vienna, the Computational Proteomics subunit of the Bioinformatics Research Group in Hagenberg has focused on the development of algorithms to identify proteins and peptides in biological samples. This has led to the emergence of the MS Amanda algorithm, a database search engine specially designed for high-resolution data sets and perfectly capable of identifying chimeric spectra. In addition, we are currently working on a library search engine, MS Ana, that is able to identify peptides based on a previously created library of mass spectra with known peptide identifications. To complement that, a search engine to identify peptides connected with a cleavable cross-linker, called MS Annika, is also in progress.