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 ...

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 ...

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 ...

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 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 collaborative project has created a comprehensive guide to help standardize spatial transcriptomics practices. Spatial transcriptomics provides a unique perspective on the genes that cells express ...

Conventional transcriptomic techniques have revealed much about gene expression at the population and single-cell level—but they overlook one crucial factor: spatial context. In musculoskeletal ...

Researchers at MD Anderson Cancer Center have used spatial transcriptomics to chart the internal architecture of ...