Dr. Mathias Gorski
Lehrstuhl für Genetische Epidemiologie
- E-Mail Adresse: mathias.gorski(at)ur.de (öffnet Ihr E-Mail-Programm)
- Tel: 0941 944 5215 (startet einen Telefonanruf, wenn Ihr Gerät dies zulässt)
- Standort: D3, 4.17
- Wichtige Informationen: Dr. rer. physiol.
Curriculum Vitae
- 03/2016 PhD (Doctor of Biomedical Sciences)
- Since 2013 Research Associate, Chair of Genetic Epidemiology, University of Regensburg, Faculty of Medicine, Regensburg
- 2010–2013 Research Associate, Institute of Epidemiology and Preventive Medicine, University of Regensburg, Faculty of Medicine, Regensburg
- 2006–2009 Research Associate, Fraunhofer Institute for Integrated Circuits IIS, Communications Networks Department
- 2005–2006 Diploma thesis at the Fraunhofer Institute for Integrated Circuits IIS, Communications Networks Department
- 2001–2006 Studies in Computer Science, Friedrich-Alexander University Erlangen–Nuremberg (FAU)
Research Focus
- Genetic epidemiology of complex diseases using large-scale population-based datasets
- Genome-wide association studies (GWAS) and genome-wide age-interaction analyses (GWAMAS)
- Genetic determinants of kidney function and chronic kidney disease (CKD)
- Collaborative research within international consortia, including the CKDGen Consortium (https://ckdgen.imbi.uni-freiburg.de/) and the International AMD Genomics Consortium (http://eaglep.case.edu/iamdgc_web/)
- Investigation of genetic effects across the life course
Technical Expertise
- Programming and scripting: R, Python, C/C++, and Java for scientific computing
- High-performance computing (HPC): large-scale computational workflows with Slurm
- Server and multi-user systems administration: installation, configuration, and maintenance of Debian based infrastructure
- Software design and data analysis pipelines: development of scalable pipelines for high-dimensional data
- Parallel and high-throughput computing: implementation and operation of analysis workflows for large-scale data processing
Selected publications
- Gorski, Mathias; Wiegrebe, Simon; Burkhardt, Ralph; Behr, Merle; Küchenhoff, Helmut; Stark, Klaus J. et al. (2025): Bias-corrected serum creatinine from UK Biobank electronic medical records generates an important data resource for kidney function trajectories. In: Scientific reports 15 (1), S. 3540. DOI: 10.1038/s41598-025-85391-7.
- Gorski, Mathias; Grunin, Michelle; Herold, Janina M.; Fröhlich, Benedikt; Behr, Merle; Wheeler, Nicholas et al. (2025): Diverse-Ancestry GWAS of Age-Related Macular Degeneration on 16,108 Examined Cases and 18,038 Controls.
- Gorski, Mathias; Rasheed, Humaira; Teumer, Alexander; Thomas, Laurent F.; Graham, Sarah E.; Sveinbjornsson, Gardar et al. (2022): Genetic loci and prioritization of genes for kidney function decline derived from a meta-analysis of 62 longitudinal genome-wide association studies. In: Kidney international 102 (3), S. 624–639. DOI: 10.1016/j.kint.2022.05.021.
- Gorski, Mathias; Jung, Bettina; Li, Yong; Matias-Garcia, Pamela R.; Wuttke, Matthias; Coassin, Stefan et al. (2021): Meta-analysis uncovers genome-wide significant variants for rapid kidney function decline. In: Kidney international 99 (4), S. 926–939. DOI: 10.1016/j.kint.2020.09.030.
- Gorski, Mathias; Günther, Felix; Winkler, Thomas W.; Weber, Bernhard H. F.; Heid, Iris M. (2019): On the differences between mega- and meta-imputation and analysis exemplified on the genetics of age-related macular degeneration. In: Genetic epidemiology 43 (5), S. 559–576. DOI: 10.1002/gepi.22204.
- Gorski, Mathias; van der Most, Peter J.; Teumer, Alexander; Chu, Audrey Y.; Li, Man; Mijatovic, Vladan et al. (2017): 1000 Genomes-based meta-analysis identifies 10 novel loci for kidney function. In: Scientific reports 7, S. 45040. DOI: 10.1038/srep45040.
- Fritsche, Lars G.; Igl, Wilmar; Bailey, Jessica N. Cooke; Grassmann, Felix; Sengupta, Sebanti; Bragg-Gresham, Jennifer L., Burdon K., Hebbring S., Wen C, Gorski M et al. (2016): A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants. In: Nature genetics 48 (2), S. 134–143. DOI: 10.1038/ng.3448.