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Head of the Institute of Medical Bioinformatics




Prof. Dr. Tim Beissbarth

Institute of Medical Bioinformatics
Goldschmidtstr. 1
37077 Göttingen

Phone : +49 - (0)551 - 39 14912


About us

The research focus of the Institute of Medical Bioinformatics at the University Medical Center Göttingen is on methods in Medical Bioinformatics and applications in Systems Medicine. We aim to develop methods to statistically analyze and understand especially high-dimensional data sets coming from biomedical research and applications. Especially, genomics, transcriptomics, proteomics and other omics as well as the integrative analysis and meaningful interpretation of such different data types pose major challenges for method development, where the methods have to be tailored towards the specific applications. We therefore apply methods from the area of machine learning as well as statistical computing. Like our research, our teaching in bioinformatics is focused on methods for high-throughput data analysis and interpretation. We teach a wide range of students from different fields such as in medicine, biology, biochemistry, molocular medicine, applied statistics, computer sciences and data science. 

Background

The fields of bioinformatics and systeme medicine are modern and expanding fields with increasing importance in medicine. They are central importance, especially for the successful establishment of research and clinical infrastructures for personilized medicine. Measurements of different data in individual patients are increasingly becoming the core of a systematic understanding of disease and thus serve to improve diagnosis and therapy. The development of Systems Medicine approach requires strong interdisciplinary cooperation. Research in medical bioinformatics and systems medicine for the analysis of high-throughput data provides a better understanding of disease mechanisms. The goal of our research is to develop methods for the analysis, integration and interpretation of biomedical data in order to make them usable in a clinical context. The applications of these methods are in the field of systems medicine, e.g. diagnosis of diseases using models of signaling pathways and omics data, and in the field of personalized medicine, e.g. therapy decisions in molecular tumor boards.