The field of spatial transcriptomics utilizes technologies that map gene expression data to specific cellular locations within tissues. While traditional RNA sequencing methods generate quantitative ...

Applying single-cell RNA sequencing has led researchers to be able to profile the entire transcriptome of cells. However, these transcriptomes prove difficult to link back to their original location ...

Researchers reveal the intricate molecular landscape of triple-negative breast cancer (TNBC), uncovering actionable spatial archetypes and gene signatures that pave the way for personalized therapies ...

Initially, cells are dissociated from liver tissues into single-cell suspensions using in vivo enzymatic perfusion or ex vivo digestion methods. The cells of interest are then enriched from the ...

This figure shows how the STAIG framework can successfully identify spatial domains by integrating image processing and contrastive learning to analyze spatial transcriptomics data effectively.

Researchers at the Max Delbrück Center have developed an open-source spatial transcriptomics (ST) platform, called Open-ST, that creates 3D molecular maps from patient tissue samples with subcellular ...