Publications

Janne Pott, Valentin Schlegel, Andrej Teren, Katrin Horn, Holger Kirsten, Christina Bluecher, Juergen Kratzsch, Markus Loeffler, Joachim Thiery, Ralph Burkhardt, and Markus Scholz. Genetic regulation of PCSK9 (proprotein convertase subtilisin/Kexin type 9) plasma levels and its impact on atherosclerotic vascular disease phenotypes. Circ. Genom. Precis. Med., (11)5:e001992, Ovid Technologies (Wolters Kluwer Health), May 2018. [PUMA: genome-wide study atherosclerosis; association]

Thomas W Winkler, Felix Grassmann, Caroline Brandl, Christina Kiel, Felix Günther, Tobias Strunz, Lorraine Weidner, Martina E Zimmermann, Christina A Korb, Alicia Poplawski, Alexander K Schuster, Martina Müller-Nurasyid, Annette Peters, Franziska G Rauscher, Tobias Elze, Katrin Horn, Markus Scholz, Marisa Cañadas-Garre, Amy Jayne McKnight, Nicola Quinn, Ruth E Hogg, Helmut Küchenhoff, Iris M Heid, Klaus J Stark, and Bernhard H F Weber. Genome-wide association meta-analysis for early age-related macular degeneration highlights novel loci and insights for advanced disease. BMC Med. Genomics, (13)1:120, Springer Science and Business Media LLC, August 2020. [PUMA: macular study (IAMDGC); consortium association TYR; Genome-wide Age-related degeneration (GWAS); UK Machine-learning; AMD CD46; (UKBB) Early genomics (AMD); phenotyping; Meta-analysis; biobank Automated AMD; International]

Patrick Ebel, Florian Brokhausen, and Andreas Vogelsang. The Role and Potentials of Field User Interaction Data in the Automotive UX Development Lifecycle: An Industry Perspective. 12th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, 141–150, Association for Computing Machinery, New York, NY, USA, 2020. [PUMA: systems study in-vehicle interview user information experience] URL

Ali Al-Fatlawi, Negin Malekian, Sebastián Garc\'ıa, Andreas Henschel, Ilwook Kim, Andreas Dahl, Beatrix Jahnke, Peter Bailey, Sarah Naomi Bolz, Anna R Poetsch, Sandra Mahler, Robert Grützmann, Christian Pilarsky, and Michael Schroeder. Deep learning improves pancreatic cancer diagnosis using RNA-based variants. Cancers (Basel), (13)11:2654, MDPI AG, May 2021. [PUMA: cancer; pancreatitis; study transcriptome-wide deep learning; topic_lifescience association pancreatic chronic]