https://www.sciencedaily.com/releases/2022/02/220202111804.htm

According to Fabian Theis, Head of the Computational Health Center at Helmholtz Munich and Professor for Mathematical Modelling of Biological Systems at TUM: "It's been a crazy 4 weeks, with many of our scientific stories and methods coming to fruition in that same time window. Our research groups focuses on using single cell genomics to understand the origin of disease in a mechanistic fashion -- for this we leverage and develop machine learning approaches to better represent this complex data. In the three new paper, we worked on single cell data integration, trajectory learning and spatial resolution, respectively. Besides the applications shown in the papers, we expect to support the next generation of single-cell research towards disease understanding."

Here are the latest solutions developed by Helmholtz Munich and TUM researchers: