In this talk, I will focus on recent developments in the emerging field of Spatial Transcriptomics, where we study the spatial aspects of gene expression. In recent years, it has become apparent that not only the number of RNA molecules, but also their spatial distribution inside cells is important for understanding this fundamental process. Here, I will present methods to characterize spatial patterns by machine learning approaches and simulation of realistic images.

This presentation is part of Minisymposium “MS66 - Spatial statistics in microscopy imaging”
organized by: Charles Kervrann (Inria) .

Authors:

Walter Thomas (CBIO, Mines ParisTech)

Keywords:

image segmentation, machine learning