A team of Vanderbilt researchers has released a new benchmarking study that aims to assist scientists in selecting the most effective methods for analyzing spatial transcriptomics (ST) data. ST ...

Spatial transcriptomics data analysis increasingly depends on artificial intelligence (AI) to convert raw, location-tagged gene expression readings into a usable map of tissue biology. Unlike ...

Single-cell transcriptome and spatial transcriptomics reveal KRAS-driven stemness and immune-suppressive microenvironment in a rare ampullary carcinoma ...

Biological tissues are made up of different cell types arranged in specific patterns, which are essential to their proper functioning. Understanding these spatial arrangements is important when ...

Single-cell transcriptomics has revolutionized the study of cellular diversity and function by enabling gene expression analysis at single-cell resolution. The technique is crucial for understanding ...

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 ...

A Vanderbilt Health and TGen team applied spatial transcriptomics to heart transplant biopsies, uncovering cellular programs linked to rejection, therapy response, and cardiac allograft vasculopathy.