Learning objectives

• Put spatial omics data into a spatial statistics context (concepts, intuition)
• Learn about how spatial statistics approaches can be applied to the analysis of spatial omics datasets
• Learn about structure-based analysis of spatial omics data

Speaker biography

With formal training and broad experience as a statistician, Prof. Robinson has been at the interface of biology, statistics and informatics for almost 25 years. The Robinson Statistical Bioinformatics group at UZH has three overlapping research themes: i) collaborative data analysis; ii) statistical methods and software development, and; iii) technology and methodology benchmarking. Their core strength is in the development and use of advanced statistical techniques to robustly process and interpret large genomic datasets, most recently with focus on tools for the analysis of single cell and spatial omics datasets.