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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

09.01.2023

Björn Ommer

LMU Munich

Title: "Deep Generative Models and their Application in the Life Sciences"

Time: 11:30 CET

Online: Click here to join

 

23.01.2023

Joergen Kornfeld

Research Group Leader

Max Planck Institute for Biological Intelligence

Title: "Reconstructing neural networks with neural networks: How machine learning enabled large-scale connectomics at synaptic resolution."

Time: 11:30 CET

Click here to join

Publications

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2023 Scientific Article in The Lancet Regional Health - Europe

Thuesen, A.C.B. ; Stæger, F.F. ; Kaci, A. ; Solheim, M.H. ; Aukrust, I. ; Jørsboe, E. ; Santander, C.G. ; Andersen, M.K. ; Li, Z. ; Gilly, A. ; Stinson, S.E. ; Gjesing, A.P. ; Bjerregaard, P. ; Pedersen, M.L. ; Larsen, C.V.L. ; Grarup, N. ; Jørgensen, M.E. ; Zeggini, E. ; Bjørkhaug, L. ; Njølstad, P.R. ; Albrechtsen, A. ; Moltke, I. ; Hansen, T.

A novel splice-affecting HNF1A variant with large population impact on diabetes in Greenland.

2023 Scientific Article in Nucleic Acids Research

Nassar, L.R. ; Barber, G.P. ; Benet-Pages, A. ; Casper, J. ; Clawson, H. ; Diekhans, M. ; Fischer, C. ; Gonzalez, J.N. ; Hinrichs, A.S. ; Lee, B.T. ; Lee, C.M. ; Muthuraman, P. ; Nguy, B. ; Pereira, T. ; Nejad, P. ; Perez, G. ; Raney, B.J. ; Schmelter, D. ; Speir, M.L. ; Wick, B.D. ; Zweig, A.S. ; Haussler, D. ; Kuhn, R.M. ; Haeussler, M. ; Kent, W.J.

The UCSC genome browser database: 2023 update.

Contact

Dr. Anna Sacher

Director of Operations

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