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 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. 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 Erik Strauß Gay Tube in healthy and disease state to build AI-driven analytics platforms for multimodal data, in particular from genomics and diverse imaging modalities. 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. Computer systems can already independently analyze health data, learn from it and even derive therapy recommendations. Which opportunities this means for patients and what research needs to apply artificial intelligence in practice. A research team led by Dr. A team led by Prof. Fabian Theis, Director of the Computational Health Center and the Institute of Computational Biology at Helmholtz Munich, has developed Spapros, a computational pipeline set to transform the design of spatial transcriptomics…. On November 25,Helmholtz Munich hosted an inspiring evening at the Bergson Kunstkraftwerk in Munich. The event, titled "Fit for the Future — How can AI revolutionize Health and Medicine? Carsten Marr…. In a novel international study, researchers have created the Human Neural Organoid Cell Atlas HNOCA. This atlas integrates 1. Helmholtz Munich launches the Helmholtz Munich Imputation Server, providing an imputation service for researchers based in the European Union EU and beyond. Imputation is the statistical inference of unobserved genotypes and plays a pivotal role in…. Zeynep Akata is selected as one of the leading "Top 40 Under 40". Read her compelling interview! Stefan Bauer advocates for the democratization and transparency of machine learning research. Read more in this Interview with the AI-expert and Senior PI. The German Federal Ministry of Education and Research BMBF is funding the new collaborative project CausalNet with nearly two million euros. The goal: to develop a new generation of machine learning over the next three years that can understand…. A new computational tool called Moslin is gaining attention in biomedical research by helping scientists better understand how Erik Strauß Gay Tube make decisions during critical biological processes like development, disease progression, and tissue healing. A team of researchers has unveiled Tumoroscope, a computational method that offers unprecedented insight into the spatial evolution of tumors and the intricate behaviors of cancer cell populations, known as clones. Published in Nature Communications,…. The Helmholtz Association has announced the winners of its second Helmholtz Foundation Model Initiative call, with Helmholtz Munich playing a key role in two of the three selected projects. These innovative projects — VirtualCell and PROFOUND — are…. Interview with Prof. Matthias Tschöp about health research and prevention with cutting-edge tools. A team of computational biologists from Helmholtz Munich has been honored with the "Frontiers of Science" award at the International Congress of Basic Science ICBS in Beijing. Researchers Fabian Theis, Alexander Wolf, and Philipp Angerer received…. Led by Helmholtz Munich, scientists have developed an accessible software solution specifically designed for the analysis of complex medical health data.
Computational Health Center
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