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 ...

Spatial transcriptomics offers a revolutionary approach to understanding the tumor microenvironment (TME) in solid tumors by preserving the spatial context of gene expression, which is crucial for ...

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 ...

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 new study generated one of the most comprehensive spatially resolved transcriptomic maps of cellular communication between ...

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 ...

U.S. Spatial Genomics and Transcriptomics Market to Grow from USD 0.26 Billion to USD 0.71 Billion by 2035, While Europe ...

Spatial transcriptomics data from osteosarcoma cells. Left) A spatial map of the transcriptome segmented into individual cells using machine learning, with each dot representing a RNA transcript and ...

This figure shows how the STAIG framework can successfully identify spatial domains by integrating image processing and contrastive learning to analyze spatial transcriptomics data effectively.