Data Science

In the research area Data Science, we focus on the development and application of data-driven methods for solving biological, medical, and technical problems. In close cooperation with our partners from research and industry, we develop algorithms for preprocessing and analyzing data using statistical methods and machine learning, as well as visualizing and interpreting the results. For example, within the project LeiVMed Online we develop a platform for benchmarking and visualizing data of treatments of patients in hospitals and developing prediction models for the outcome of treatments.

In many of our projects, we see the need for customized data processing pipelines due to the heterogeneity and complexity of data structures in real world processes and systems. We use applied statistics as well as numerous machine learning approaches, including black box methods (deep neural nets, random forests, gradient boosted trees, etc.) and white box methods (symbolic regression by genetic programming). We build our knowledge discovery pipelines on a variety of different frameworks, especially python scikit-learn, tensorflow, pytorch, MATLAB, and HeuristicLab.



Selected Publications

Selected Projects


The project SESAM is sponsored by the FWF (within the translational research programme) and executed as joint basic research project of the group of Karl Mechtler at IMP Vienna and members of the Bioinformatics Research Group Hagenberg. SESAM continues the research started in the MS Amanda project and pursues the development of the peptide and protein identification algorithm MS Amanda.

Within this project we focus on the following aspects:

* Identification of hybrid spectra

* Consideration of many post-translational modifications

* Extraction of features for characterizing tandem mass spectra


The implementation of MS Amanda for Proteome Discoverer can be found online:


Prof.(FH) DI Dr. Stephan Winkler


DI(FH) Viktoria Dorfer MSc

Sebastian Dorl MSc


2013 - 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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