Working Group Statistical Methods in Epidemiology

Welcome to the website of the working group Statistical Methods in Epidemiology in the Department of Medical Biometrics, Informatics and Epidemiology (IMBIE) at the University of Bonn.

Most Recent Publications

• Lyon G J, Vedaie M, Beisheim T, Park A, Marchi E, Gottlieb L, Hsieh T, Klinkhammer H, Sandomirsky K, Cheng H, Starr L J, Preddy I, Tseng M, Li Q, Hu Y, Wang K, Carvalho A, Martinez F, Caro-Llopis A, Gavin M, Amble K, Krawitz P, Marmorstein R and Herr-Israel E (2023): Expanding the phenotypic spectrum of NAA10-related neurodevelopmental syndrome and NAA15-related neurodevelopmental syndrome. European Journal of Human Genetics. https://doi.org/10.1038/s41431-023-01368-y.
• Schmidt A, Röner S, Mai K, Klinkhammer H, Kircher M and Ludwig K U (2023): Predicting the pathogenicity of missense variants using features derived from AlphaFold2. Bioinformatics. https://doi.org/10.1093/bioinformatics/btad280.
• Aldisi R, Hassanin E, Sivalingam S, Buness A, Klinkhammer H, Mayr A, Fröhlich H, Krawitz P and Maj C (2023): Gene-based burden score indentify rare variant associations for 28 blood biomarkers. BMC Genomic Data. https://doi.org/10.21203/rs.3.rs-2271894/v1.
• Duenas N, Klinkhammer H, Bonifaci N, Spier I, Mayr A, Hassanin E, Diez-Villanueva A, Moreno V, Pineda M, Maj C Capella G, Aretz S and Brunet J (2023): Ability of a polygenic risk score to refine colorectal cancer risk in Lynch syndrome. Journal of Medical Genetics. doi: 10.1101/2023.04.20.23288850.
• Balestra C, Maj C, Müller E and Mayr A (2023): Redundancy-aware unsupervised ranking based on game theory: Ranking pathways in collections of gene sets. PloS one. https://doi.org/10.1371/journal.pone.0282699.
• Strömer A, Klein N, Staerk C, Klinkhammer H and Mayr A (2023): Boosting Multivariate Structured Additive Distributional Regression Models. Statistics in Medicine. arXiv preprint arXiv:2207.08470.
• Klinkhammer H, Staerk C, Maj C, Krawitz P M and Mayr A (2023): A statistical boosting framework for polygenic risk scores based on large-scale genotype data. Frontiers in Genetics. 13: 1076440.
• Maj C, Staerk C, Borisov O, Klinkhammer H, Yeung M W, Krawitz P, Mayr A (2022): Statistical learning for sparser fine-mapped polygenic models: the prediction of LDL-cholesterol. Genetic Epidemiology. 46(8): 589-603.

We are interested in the development of new methodology in the field of computational statistics and in the applied analysis of biomedical and epidemiological data.

• Methodological research
  • Statistical boosting
  • GAMLSS (generalized additive models for location, scale and shape)
  • Quantile regression
  • Prediction inference and prediction intervals
  • Variable selection for high-dimensional data

• Applications
  • Paediatric and Perinatal Epidemiology
  • Eating disorders
  • Schizophrenia and depression
  • Medical Internet research
  • Genomics

The IMBIE offers statistical consulting for scientific staff and doctoral candidates (please see Statistische Beratung). For other projects, please do not hesitate to contact us if you are interested in a cooperation. We are always open to new areas of application.

We also offer various topics for Bachelor or Master theses with a focus on statistical methodology. Please get in touch with us if you are interested.