Three papers in Nature Methods resulting from work carried out at Theis lab and one review in Nature Biotechnology published.
A bumper-crop of publications
The past weeks have seen a flurry of publications in high-impact journals resulting from the work carried out at Helmholtz AI scientific director Fabian Theis’ lab. Research at the Theis lab focuses on using single cell genomics to understand the origin of disease in a mechanistic fashion, and for this researchers leverage and develop machine learning approaches to better represent complex data.
“In the three new papers, 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,” says Theis about the papers. What’s more, in the latest issue of the journal Nature Biotechnology, researchers from the Theis lab and Aviv Regev, the vice president of research and development at Genentech, review the conceptual and methodological state of the art of the spatial analysis of tissues and after lading the cover page of the previous issue for “single-cell data in context”.
Theis is Head of the Computational Health Center at Helmholtz Munich, the Helmholtz AI unit that focuses on health. In close cooperation with the Technical University of Munich (TUM), his team uses artificial intelligence and machine learning to enable medical innovations for a healthier society.
Links to the original publications
- Lücken et al. 2022: Benchmarking atlas-level data integration in single-cell genomics. Nature Methods, DOI: 10.1038/s41592-021-01336-8.
- Lange et al. 2022: CellRank for directed single-cell fate mapping. Nature Methods, DOI: 10.1038/s41592-021-01346-6.
- Palla, Spitzer et al. 2022: Squidpy: a scalable framework for spatial omics analysis. Nature Methods, DOI: 10.1038/s41592-021-01358-2.
- Palla et al. 2022: Spatial components of molecular tissue biology, Nature Biotechnology, DOI: 10.1038/s41587-021-01182-1
- Press release by Helmholtz Munich: Predicting cell fates: Researchers develop AI solutions for next-gen medical research