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.

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 ...

Mapping biological networks in lung adenocarcinoma using transcriptomic analysis to identify prognostic biomarkers and therapeutic targets.

Spatial transcriptomics is a technique that provides information about gene expression patterns within intact tissues. This technology employs various methodologies, including in situ sequencing (ISS) ...

In the brain, location is everything. And the throngs of cells that live there are nothing without the billions of distinct connections between them. Although scientists can use single-cell ...

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 ...

In a recent study published in Nature, researchers investigate the spatial organization of cancer cells and the tumor microenvironment by analyzing over one hundred tumor sections across six types of ...

This eBook cuts through the complexity of spatial techniques, featuring a series of interviews with pioneers in the field, and peer-reviewed research from the Taylor & Francis journal portfolio. This ...

Biological tissues are made up of different cell types arranged in specific patterns, which are essential to their proper ...