Researchers from Baltimore-based Johns Hopkins have created a machine learning algorithm, SpaceMarkers, that can identify molecular interactions among cells in and around tumors.
SpaceMarkers uses spatial transcriptomics, a type of technology that helps measure gene expression within a tissue sample using the genes' locations in cells, according to a May 11 press release from Johns Hopkins.
The tool then uses spatial transcriptomic data to locate regions of high activity from individual cell types and identifies molecular changes from the interaction of two cell types.
By using the tool, researchers said they will be able to better understand intercellular interactions in the tumor microenvironment and the molecular profiles of individual cells.
In addition, this tool provides reserarchers with insights into a tumor's progression.