• 10/2017: Graduation from the Johannes Kepler University Linz with the degree Dr. rer. nat. (PhD)
  • Thesis: Analyzing NGS Data with Machine Learning - From IBD Segments to Copy Number Variations
• 2013 - 2017: PhD Studies Bioinformatics, Johannes Kepler University Linz
• 02/2013: Graduation from the Johannes Kepler University Linz with the degree MSc.
  • Thesis: IBD Mapping of Autism Microarray Data - Beyond Linkage and Association Mapping
• 2010 - 2013: Master Studies Bioinformatics, Johannes Kepler University Linz
• 07/2010: Graduation from the Medical University Vienna with the degree Dr. med. univ. (MD)
• 2008 - 2009: Diploma theses at the Institute of Medical Genetics, Vienna (Proportion of SPRED1 mutation carriers in NF1-negative children with café-au-lait spots)
• 2004 - 2010: Medical studies, Medical University Vienna
• 06/2004: Matura (high school graduation) at BG/BRG Khevenhüller with distinction
• 1996 - 2004: Secondary School: BG/BRG Khevenhüller, Linz
• 1992 - 1996: Elementary School: Volksschule Römerberg, Linz

• Machine Learning
• Deep Learning
• Genetics
• Sequence Analysis
• Copy Number Variations
• Disease Associations
• Population Genetics
• Identity by Descent (IBD) Detection

panelcn.mops R package: CNV detection tool for targeted NGS panel data.

• Available at Bioconductor: panelcn.mops, öffnet eine externe URL in einem neuen Fenster 
• Github: https://github.com/bioinf-jku/panelcn.mops, öffnet eine externe URL in einem neuen Fenster

For more information see http://bioinf.jku.at/software/panelcnmops/, öffnet eine externe URL in einem neuen Fenster

• Povysil G., Tzika A., Vogt J., Haunschmid V., Messiaen L., Zschocke J., Klambauer G., Hochreiter S. and Wimmer K. (2017). panelcn.MOPS: Copy number detection in targeted NGS panel data for clinical diagnostics. Human Mutation 38 (7): 889-897. doi:10.1002/humu.23237 Abstract, öffnet eine externe URL in einem neuen Fenster
• Clevert D.-A., Unterthiner T., Povysil G and Hochreiter S. (2017). Rectified Factor Networks for Biclustering of Omics Data. Bioinformatics, 33 (14): i59-i66. doi:10.1093/bioinformatics/btx226 Abstract, öffnet eine externe URL in einem neuen Fenster
• Povysil G, Hochreiter S. (2016). IBD Sharing between Africans, Neandertals, and Denisovans.Genome Biology and Evolution 8 (12): 3406-3416. doi:10.1093/gbe/evw234 Abstract, öffnet eine externe URL in einem neuen Fenster
• Povysil G, Hochreiter S. (2014). Sharing of very short IBD segments between humans, Neandertals, and Denisovans. bioRxiv.

• ÖGH 2016, Vienna, Austria: panelcn.MOPS: CNV detection in targeted panel sequencing data for diagnostic use
• ASHG 2015, Baltimore, MD, USA: IBD sharing in the 1000 Genomes Project Phase 3 data reveals relationships from Neandertals to present day families

• NIPS Workshop on ML in Computational Biology 2017, Long Beach, CA, USA: HapRFN: Rectified Factor Networks for identifying short IBD segments
• WiML 2017, Long Beach, CA, USA: panelcn.MOPS - a mixture of Poissons model for copy number detection
• ESHG 2017, Copenhagen, Denmark: panelcn.MOPS: CNV detection in targeted NGS panel data for clinical diagnostics
• WiML 2016, Barcelona, Spain: HapRFN: a deep learning method for identifying short IBD segments
• ASHG 2016, Vancouver, Canada: panelcn.MOPS: CNV detection in targeted panel sequencing data for diagnostic use
• ASHG 2015, Baltimore, MD, USA: panelcn.MOPS reaches clinical standards as a CNV detection tool for targeted panel sequencing data
• SMBE 2015, Vienna, Austria: Early Interbreeding between Ancestors of Humans, Neandertals, and Denisovans within Africa
• ASHG 2014, San Diego, CA, USA: Population specific patterns of novel haplotype groups at the PAH locus
• ASHG 2013, Boston, MA, USA: IBD Mapping of Autism Microarray Data
• ASHG 2012, San Francisco, CA, USA: Detection of identity by descent based on rare variants
• HGV 2012, Shanghai, China: Identifying IBD tracts that are tagged by rare variants
• ISMB 2012, Long Beach, CA, USA: Comparison of IBD detection methods with a focus on rare variants

• Summer semester 2015 - 2016: Exercises in Theoretical Concepts of Machine Learning & Exercises in Machine Learning: Unsupervised Techniques
• Summer semester 2014 and 2017: Special Topics on Bioinformatics: Population genetics
• Summer semester 2013: Exercises in Theoretical Bioinformatics and Machine Learning
• Winter semester 2012/13 - 2017/18: Exercises in Sequence Analysis and Phylogenetics