A researcher's guide to spatial transcriptomics: how sequencing- and imaging-based methods work, and how to choose a platform ...

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 ...

Researchers have developed Fullscope-seq, a long-read spatial transcriptomics platform that maps alternative transcript isoforms within intact tissues at single-cell resolution - opening new ...

Single-cell RNA transcriptomics allows researchers to broadly profile the gene expression of individual cells in a particular tissue. This technique has allowed researchers to identify new subsets of ...

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 ...

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 ...

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 ...

Fei Chen and Chenlei Hu at the Broad Institute of MIT and Harvard have developed a new imaging-free spatial transcriptomics technology that tracks the diffusion of DNA barcodes between beads in an ...

Knowing the location of a gene within intact tissue or a single cell allows scientists to unlock unknown cellular functions. This information is often lost in most genetic sequencing techniques, but ...