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Computational Biology for Infection Research
The Department of “Computational Biology for Infection Research” studies the human microbiome, viral and bacterial pathogens, and human cell lineages within individual patients by analysis of large-scale biological and epidemiological data sets with computational techniques. Focusing on high throughput meta’omics, population genomic and single cell sequencing data, we produce testable hypotheses, such as sets of key sites or relevant genes associated with the presence of a disease, of antibiotic resistance or pathogenic evasion of immune defense. We interact with experimental collaborators to verify our findings and to promote their translation into medical treatment or diagnosis procedures. To achieve its research goals, the department also develops novel algorithms and software.
Biostatistics
High-Throughput-technologies generate large amounts of data. The drawback: these biological and medical data must be processed to results with statistical methods and models. Concepts from robust and computational statistics as well as visualisation techniques help to better understand, estimate and cope with the uncertainty and strong variation that are often inherent in biological and medical data. The project group „Biostatistics“ is part of the research group „Cellular Proteome Research” which is led by Lothar Jänsch.
Experimental Immunology
Immune cell populations are characterized by a high degree of heterogeneity to enable efficient and specialized responses to the diverse set of pathogens. This is particularly true for cells of the adaptive immune system, but also innate immune cell populations are heterogeneous and can adapt to different environmental conditions. Adaptation of immune cells is often associated with epigenetic alterations that lead to the fixation of gene expression patterns, finally resulting in cells with highly specialized fates, phenotypes and functional properties.
