The Department of Genomic Statistics and Bioinformatics is involved in the planning and execution of research projects on biomedical issues with molecular markers as well as the biostatistical and bioinformatic analysis of the data. The research questions relate to possible causes of disease, prediction of disease, and models for diagnosis, risk group assignment, or prognosis of disease progression. They often involve aspects of personalized (or stratified) medicine.
One focus of our work is the application and development of methods in the field of statistical modeling and machine learning, taking into account high-dimensional genomic and other molecular markers. Furthermore, we deal with complex study designs, so-called multi-omics analyses (with different molecular markers) and meta-analyses, in which several studies are combined. In doing so, we work closely with clinical cooperation partners from different fields as well as in research networks at the University Medical Center Mainz and in a national and international context.
The methodological spectrum of the Genomic Statistics Group includes genome-wide association studies using sequencing as well as genotyping array (chip) data. This also includes consideration of population genetic aspects, quality control and performance of genome-wide imputation. Furthermore, we deal with the analysis of mitochondrial DNA as well as methods for genetic analysis in families, which we implement in computer programs and apply to projects on various diseases.
The Bioinformatics group is concerned with the development of methods and software for the analysis of high-dimensional molecular data, with a focus on gene expression data (RNA-seq, also with single cell resolution). To this end, we develop new approaches and software packages, including interactive applications, for statistical modeling, machine learning, integration as well as interpretation of transcriptome, epigenome, genome and proteome datasets.
Consulting and collaborative services are available for planning and evaluating biomedical and clinical research projects in bioinformatics and genomic statistics. We supervise interns, bachelor and master theses primarily in the fields of bioinformatics, bio/statistics and epidemiology. If you are interested, please contact us directly.