GRK 2624:  Biostatistical methods for high-dimensional data in toxicology

• Subject Area: Medicine
• Term: since 2021
• Website: Homepage
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 427806116

The goal of the Research Training Group (RTG) is the development, evaluation, and application of statistical methods for answering complex toxicological questions. In toxicology, there is an immense need for methods to analyse large data sets, especially in the field of omics data, which have been increasingly collected in recent years. The potential of these data to gain new insights is often not fully exploited due to a lack of suitable statistical methods. In the RTG, the researchers develop such methods adapted to questions in environmental and pharmaceutical toxicology and learn how to apply them appropriately. These statistical methods are often generic, but their interpretation is tailored to specific toxicological questions. The research programme is composed of the three main project areas regression, prediction, and integration. In the projects on regression and prediction, the effects of exposures on health are of particular interest. In the regression projects, omics data are usually considered as covariates in the regression model, while in the prediction projects they are usually considered as target variables, which in turn serve as surrogates for health. In the area integration, different molecular data types are collected and simultaneously analysed. A focus of the RTG is to adapt statistical methods for the analysis of low-dimensional toxicological data to high-dimensional data and to develop new methods targeted to the specific research problems with high-dimensional data. The high-dimensional nature of the data can be exploited to advantage. This is often achieved by dimension reduction techniques or by combining information contained in groups of genes or proteins. This general concept is applied in a variety of ways in the research projects. For the qualification programme of the RTG, emphasis is placed on interdisciplinary elements that combine statistics and toxicology. Doctoral and postdoctoral researchers gain an outstanding qualification profile, based on scientific training in biostatistics, toxicology and statistical analysis of high-dimensional molecular data as well as courses on transferable skills. Doctoral researchers are jointly supervised by researchers from statistics and toxicology, and they benefit from the expertise of both and from established collaborations. Scientific interaction and networking is supported by a regular seminar, including lectures by international visiting researchers, and international visibility is strengthened through conference participation, longer research visits abroad, and workshop organisation.

• DFG Programme: Research Training Groups
• Applicant Institution: Technische Universität Dortmund
• Participating Institution: Heinrich-Heine-Universität Düsseldorf; Leibniz-Institut für Arbeitsforschung an der TU Dortmund; IUF - Leibniz-Institut für umweltmedizinische Forschung gGmbH; Universität zu Köln
• Spokesperson: Professor Dr. Jörg Rahnenführer
• Participating Researchers: Professor Dr. Andreas Groll; Professor Dr. Jan G. Hengstler; Dr. Carolin Herrmann; Professorin Dr. Katja Ickstadt; Professor Dr. Jean Krutmann; Professorin Dr. Kathrin Möllenhoff; Professorin Dr. Tamara Schikowski; Professorin Dr. Kirsten Schorning; Professor Dr. Holger Schwender; Professor Dr. Christian Staerk