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 ...

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 ...

Prostate cancer (PCa) is a highly prevalent malignancy, heavily characterized by complex cellular heterogeneity and highly ...

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 ...

Spatial transcriptomics provides a unique perspective on the genes that cells express and where those cells are located. However, the rapid growth of the technology has come at the cost of ...

A new study that explores gene expression during heart transplant rejection marks a step forward for precision medicine approaches to treat organ rejection.

New simulator and computational tools generate realistic ‘virtual tissues’ and map cell-to-cell ‘conversations’ from spatial transcriptomics data, potentially accelerating AI-driven discoveries in ...