A Nature Methods benchmark of 11 segmentation methods across 15 spatial transcriptomics datasets shows that algorithm and ...

Spatial transcriptomics now spans two fundamentally different measurement strategies, and the choice between them shapes every downstream result a lab will generate. Sequencing-based platforms capture ...

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 ...

A computational framework linked spatial gene-expression gradients to net-production direction under steady-state and ...

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 ...

Spatial transcriptomics technologies opened the door for new kinds of biological measurements, allowing scientists to generate detailed maps of where genes are expressed in tissue. But most methods ...

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 ...

Spatial transcriptomics has transformed brain research by preserving single-cell molecular resolution within intact tissue coordinates. The brain, organized across cortical layers, long-range ...