Computational Biology for Individualised Medicine

Infections are among the biggest threats to health and the most significant causes of death worldwide. Our aim is to reveal the host genetic risk factors and their downstream molecular pathways, which are crucial to make progress in understanding and treating infectious diseases in an individualised manner as well as to improve the identification of patients at risk. The department is part of the developing CiiM and currently housed at the TWINCORE in Hannover.

Prof Dr Yang Li


Prof Dr Yang Li

Our Research

Info graphic on the research field
The inter-individual variation of the human immune system is caused by the interaction between genetics and environmental factors.

The research department “Computational Biology for Individualised 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. We are currently working on the following areas:

Genetic regulation of molecular and immune phenotypes

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.

Integration of multi-omics

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.

Single cell genomics

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.

For information on current projects please visit the CiiM website.