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Computational Health Center

We develop novel computational tools powered by AI to accelerate discovery and translation. We apply cutting-edge computational methods to promote personalised health. Collaboratively, we develop predictive algorithms as well as mechanistic models to analyse molecular, imaging, and clinical data of human health and disease. We thus help to create innovative diagnostics and novel treatments for environmentally triggered diseases.

We develop novel computational tools powered by AI to accelerate discovery and translation. We apply cutting-edge computational methods to promote personalised health. Collaboratively, we develop predictive algorithms as well as mechanistic models to analyse molecular, imaging, and clinical data of human health and disease. We thus help to create innovative diagnostics and novel treatments for environmentally triggered diseases.

Our Research Areas

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Digital Genomics and Image Computing

We develop robust methods for analyzing big data to address key biomedical challenges and consolidate analytical approaches using innovative digital methods. In addition, we develop novel statistical methods for trans- ethnic meta-analysis, testing for pleiotropy, rare variant burden, testing, and polygenic risk score construction.

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Health AI

We develop and translate AI technologies for biomedical problems by constructing deep-learning methods and combining them with more mechanistic modeling approaches. In addition, we steer the computational aspects of developing single-cell atlases in healthy and disease state to build AI-driven analytics platforms for multimodal data, in particular from genomics and diverse imaging modalities.

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Systems Biomedicine

We develop novel computational methods for multiomic data integration of epigenomic, transcriptomic, proteomic and genetic data and advanced phenotypic/in vivo observations. In addition, we design novel approaches for efficient data combination across omics levels, maximizing the information yield across the multidimensional space of datar from genomics and diverse imaging modalities.

Further News

Upcoming Computational Health Seminars

12.12.2022

Daniel Kotlarz

KUBUS Research Center

Title: TBA

Time: 11:30 CET

Online: Click here to join

 

19.12.2022

Jakob Nikolas Kather

Professor of Clinical Artificial Intelligence
Else Kröner Fresenius Center for Digital Health
Technical University Dresden 

Title: "Artificial intelligence-based biomarkers in precision oncology"

Time: 11:30 CET

Click here to join

Publications

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2022 Scientific Article in Nature medicine

Surendran, P. ; Stewart, I.D. ; Au Yeung, V.P.W. ; Pietzner, M. ; Raffler, J. ; Wörheide, M. ; Li, C. ; Smith, R.F. ; Wittemans, L.B.L. ; Bomba, L. ; Menni, C. ; Zierer, J. ; Rossi, N. ; Sheridan, P.A. ; Watkins, N.A. ; Mangino, M. ; Hysi, P.G. ; Falchi, M. ; Spector, T.D. ; Michelotti, G.A. ; Arlt, W. ; Lotta, L.A. ; Denaxas, S. ; Hemingway, H. ; Gamazon, E.R. ; Howson, J.M.M. ; Wareham, N.J. ; Kastenmüller, G. ; Fauman, E.B. ; Suhre, K. ; Butterworth, A.S. ; Langenberg, C.

Rare and common genetic determinants of metabolic individuality and their effects on human health.

Contact

Dr. Anna Sacher

Director of Operations

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