Forschungsfokus Computational Biology for Individualized Medicine
The research group “Computational Biology for Individualized Infection Medicine” studies the interaction of genetic background and environment, and its contribution to infection and immune-related diseases.
We focus on applying and developing the computational and statistical approaches to study the effect of genetic factors on a variety of molecular levels (such as genetics, genomics, metabolomics etc.), immunological parameters and functions, and complex diseases.
Our aim is to reveal the host genetic risk factors and their downstream molecular pathways as well as to improve the identification of at-risk patients, which are crucial to make progress in understanding and treating infectious diseases in an individualized manner.
We study how genetic variation affects molecular and immune phenotypes such as gene expression, metabolites and cytokine responses to stimulations. We develop computational methods and algorithms to fully exploit high-throughput datasets from the most recent profiling technologies, e.g., causal inference and deconvolution of the overall genetic regulation effects of gene expression into relevant cell types.
We integrate large multi-omics data sets and immune profiling of patient/control cohorts to unravel the genotype-phenotype map on a genome-wide scale and built computational models for predicting immune functions and disease risk.
We apply cutting-edge techniques to study genetic regulation of gene expression in response to stimuli at single-cell resolution and we develop novel computational approaches for single-cell biology.