• Deep Learning
• Self-normalizing neural networks
• Convolutional neural networks
• Recurrent neural networks and reinforcement learning
• Machine learning methods for drug discovery
• Life science data analysis and bioinformatics

CV_Klambauer.pdf, öffnet eine Datei

• Self-Normalizing Neural Networks (2017), Günter Klambauer, Thomas Unterthiner, Andreas Mayr, and Sepp Hochreiter. Advances in Neural Information Processing Systems 30, 972--981. [PDF], öffnet eine externe URL in einem neuen Fenster.
• DeepTox: toxicity prediction using deep learning (2016), Andreas Mayr, Günter Klambauer, Thomas Unterthiner, Sepp Hochreiter, Frontiers in Environmental Science, 3:80. doi: 10.3389/fenvs.2015.00080, öffnet eine externe URL in einem neuen Fenster
• MOPS: mixture of Poissons for discovering copy number variations in next-generation sequencing data with a low false discovery rate (2012), Klambauer, G., Schwarzbauer, K., Mayr, A., Clevert, D. A., Mitterecker, A., Bodenhofer, U., & Hochreiter, S. , Nucleic Acids Research, 40(9), e69-e69. doi:10.1093/nar/gks003, öffnet eine externe URL in einem neuen Fenster
• Deep Learning as an Opportunity in Virtual Screening (2014), Thomas Unterthiner, Andreas Mayr, Günter Klambauer, Marvin Steijaert, Jörg Wegner, Hugo Ceulemans, Sepp Hochreiter, Deep Learning and Representation Learning Workshop, in conjunction with Neural Information Processing Systems (NIPS 2014), Montreal, Canada, [PDF], öffnet eine externe URL in einem neuen Fenster
• Large-scale comparison of machine learning methods for drug target prediction on ChEMBL (2018), Andreas Mayr, Günter Klambauer, Thomas Unterthiner, Marvin Steijaert, Jörg K Wegner, Hugo Ceulemans, Djork-Arné Clevert, Sepp Hochreiter, Chemical Science, [PDF], öffnet eine externe URL in einem neuen Fenster
• DeepSynergy: Predicting anti-cancer drug synergy with Deep Learning (2017), Kristina Preuer, Richard P Lewis, Sepp Hochreiter, Andreas Bender, Krishna C Bulusu, and Günter Klambauer, Bioinformatics, Advance Access. doi: 10.1093/bioinformatics/btx806, öffnet eine externe URL in einem neuen Fenster
• Prediction of human population responses to toxic compounds by a collaborative competition (2015), Federica Eduati, Lara M Mangravite, Tao Wang, Hao Tang, ... , Sepp Hochreiter, Günter Klambauer, Andreas Mayr, ... , Ivan Rusyn, Fred A Wright, Gustavo Stolovitzky, Yang Xie, and Julio Saez-Rodriguez, Nature Biotechnology, advance online publication. http://doi:10.1038/nbt.3299, öffnet eine externe URL in einem neuen Fenster.
• How adverse outcome pathways can aid the development and use of computational prediction models for regulatory toxicology (2017), Clemens Wittwehr, Hristo Aladjov, Gerald Ankley, Hugh J Byrne, Joop de Knecht, Elmar Heinzle, Günter Klambauer, Brigitte Landesmann, Mirjam Luijten, Cameron MacKay, Gavin Maxwell, ME Meek, Alicia Paini, Edward Perkins, Tomasz Sobanski, Dan Villeneuve, Katrina M Waters, Maurice Whelan,
  Toxicological Sciences, [PDF], öffnet eine externe URL in einem neuen Fenster
• Repurposed high-throughput images enable biological activity prediction for drug discovery (2017), Jaak Simm, Günter Klambauer, Adam Arany, ... & Hugo Ceulemans, bioRxiv, 108399.doi: 10.1101/108399, öffnet eine externe URL in einem neuen Fenster
• Toxicity prediction using deep learning (2015), Thomas Unterthiner, Andreas Mayr, Günter Klambauer, Sepp Hochreiter, arXiv preprint arXiv:1503.01445, PDF, öffnet eine externe URL in einem neuen Fenster
• Using transcriptomics to guide lead optimization in drug discovery projects (2015), Günter Klambauer, Bie Verbist, Liesbet Vervoort, Willem Talloen, QSTAR Consortium, Ziv Shkedy, Olivier Thas, Andreas Bender, Hinrich W.H. Göhlmann, Sepp Hochreiter, Drug Discovery Today, 20(5). http://dx.doi.org/10.1016/j.drudis.2014.12.014, öffnet eine externe URL in einem neuen Fenster.
• DEXUS: identifying differential expression in RNA-Seq studies with unknown conditions (2013), Klambauer, G., Unterthiner, T., & Hochreiter, S., Nucleic Acids Research, 41(21), e198-e198. doi:10.1093/nar/gkt834, öffnet eine externe URL in einem neuen Fenster
• Rchemcpp: a web service for structural analoging in ChEMBL, Drugbank and the Connectivity Map (2015), Günter Klambauer, Martin Wischenbart, Michael Mahr, Thomas Unterthiner, Andreas Mayr, Sepp Hochreiter, Bioinformatics, advance access. http://doi:10.1093/bioinformatics/btv373, öffnet eine externe URL in einem neuen Fenster.

• Tox21 Data Challenge (2014): Winner of the Grand Challenge, Nuclear Receptor Panel, Stress Response Panel, and six of twelve subchallenges.https://tripod.nih.gov/tox21/challenge/leaderboard.jsp, öffnet eine externe URL in einem neuen Fenster https://ncats.nih.gov/news/releases/2015/tox21-challenge-2014-winners , öffnet eine externe URL in einem neuen Fenster(Teams ``Bioinf@JKU'' and ``Bioinf@JKU-ensembleX'', Method DeepTox, öffnet eine externe URL in einem neuen Fenster)
• NIEHS-NCATS-UNC DREAM Toxicogenetics Challenge (2013): Best performing method at the prediction of average cytotoxicity.https://www.synapse.org/#!Synapse:syn1761567/wiki/60840, öffnet eine externe URL in einem neuen Fenster (Team ``Austria'')

• Backward dynamics of self-normalizing networks, Pieter-Jan Hoedt, PDF, öffnet eine externe URL in einem neuen Fenster
• Generative RNN models for molecular strings with biological activity profiles, ongoing
• Generative adversarial networks for molecular graphs, ongoing
• Improving image-based compound activity prediction with convolutional neural networks, ongoing
• Deep Learning for Drug Combination Synergy Prediction
• The Maximum Common Subgraph Kernel For Predicting Kinase Inhibitors
• Panelcn.MOPS reaches clinical standards as a copy number variation detection tool for targeted panel sequencing
• Accurate detection of tumor copy number variations in high-throughput sequencing data
• Detecting CNVs in the 1000 Genomes Project Data Using cn.MOPS and Relating the Results to Transcriptome Sequencing Data

• Since 2014: Post-Doc Researcher at Johannes Kepler University Linz
• 2014: Award of Excellence of the Austrian Ministry of Science
• 04/2014: PhD in Bioinformatics (JKU Linz)
• 2012: Austrian Life Science Award
• 2009-2014: Researcher at Johannes Kepler University Linz
• 2007-2009: Secondary School Teacher, BORG Linz and BORG Bad Leonfelden
• 07/2007: MSc in Mathematics and Biology (University of Vienna)
• 09/2006-02/2007: Studies Abroad, Universita degli Studi, Padova
• 2001-2007: Mathematics and Biology Diploma-Studies, University of Vienna

• 2017: Special Topics on Bioinformatics: Population genetics, Lecturer, Johannes Kepler University, Linz, Austria.
• 2016: Special Topics on Bioinformatics: Population genetics, Lecturer, Johannes Kepler University, Linz, Austria.
• 2014: Special Topics on Bioinformatics: Population genetics, Lecturer, Johannes Kepler University, Linz, Austria.
• 2013: Special Topics on Bioinformatics: Population genetics, Lecturer, Johannes Kepler University, Linz, Austria.
• 2012/2013: Sequence Analysis and Phylogenetics, Lecturer, Johannes Kepler University, Linz, Austria.
• 2012: Special Topics on Bioinformatics: Population genetics, Lecturer, Johannes Kepler University, Linz, Austria.
• 2011/2012: Exercises in Bioinformatics I: Sequence Analysis and Phylogenetics, Lecturer, Johannes Kepler University, Linz, Austria.
• 2011: Special Topics on Bioinformatics: Population genetics, Lecturer, Johannes Kepler University, Linz, Austria.
• 2010/2011: Exercises in Bioinformatics I: Sequence Analysis and Phylogenetics, Lecturer, Johannes Kepler University, Linz, Austria.
• 2010: Special Topics on Bioinformatics: Population genetics, Lecturer, Johannes Kepler University, Linz, Austria.
• 2009/2010: Exercises in Bioinformatics I: Sequence Analysis and Phylogenetics, Lecturer, Johannes Kepler University, Linz, Austria.
• 2008-2009: Mathematics and Biology, Secondary School Teacher, BORG Linz, Linz
• 2007-2008: Mathematics and Biology, Secondary School Teacher, BORG Bad Leonfelden, Bad Leonfelden