The research area Proteomics focuses on the analysis of proteins and peptides in biological data sets. 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 in 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, our research group has focused on the area of computational proteomics and therein 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 especially 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, also a search engine for the identification of peptides connected with a cleavable cross-linker, called MS Annika, is in progress.



Selected Publications

2019 Sebastian Dorl, Stephan M. Winkler, Karl Mechtler, and Viktoria Dorfer: MS Ana: A Spectral Library Search Engine Optimized for High-Accuracy Fragment Ion Data European Bioinformatics Community (EuBIC) Winter School 2019
2018 Sebastian Dorl, Stephan Winkler, Karl Mechtler, and Viktoria Dorfer: PhoStar: Identifying Tandem Mass Spectra of Phosphorylated Peptides before Database Search Journal of Proteome Research , Vol. 17 , pp. 290–295
2018 Viktoria Dorfer, Sergey Maltsev, Stephan M. Winkler, and Karl Mechtler: CharmeRT: Boosting peptide identifications by chimeric spectra identification and retention time prediction Journal of Proteome Research , Vol. 17 , pp. 2581–2589
2014 Viktoria Dorfer, Peter Pichler, Thomas Stranzl, Johannes Stadlmann, Thomas Taus, Stephan M. Winkler, and Karl Mechtler: MS Amanda, a Universal Identification Algorithm Optimized for High Accuracy Tandem Mass Spectra Journal of Proteome Research , Vol. 13 , pp. 3679-84

Selected Projects

MS Annika

MS Annika is a system for the identification of cross-linked peptides from tandem mass spectrometry data. MS Annika focuses on the detection of cleavable cross-linkers which allow for for the detection of linked peptides from MS2 data as opposed to more expensive MS3 studies. MS Annika is compatible with a wide variety of cleavable cross-linkers such as DSSO, DSBU, DSAU, DSBSO, PIR linkers (e.g. BDP-NHP), as well as cleavable zero-length cross-linkers (CDI). Furthermore, MS Annika also works with ion mobility data, i.e. from Bruker timsTOF instruments.

MS Annika ist fast and scalable up to proteome-wide studies. We provide an integrated workflow including peptide identification, cross-link search, and validation of cross links. The resulting cross-links can then be exported and mapped to protein structures to allow for 3D viewing of the linking sites in xiView.

For more information and to download MS Annika for Proteome Discoverer see:


DI(FH) Dr. Viktoria Dorfer MSc.


Micha Birklbauer MSc.

DI(FH) Dr. Viktoria Dorfer MSc.

Prof.(FH) DI Dr. Stephan Winkler


2018 - present

Research Areas


Research Institutions

Research Center Hagenberg

University of Applied Sciences, Upper Austria, Hagenberg Campus

Research focus

Software technology and application

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