Spatial transcriptomics and gene expression analysis represent a transformative approach in biomedical research, integrating the spatial context of tissues with high-resolution profiling of gene ...

Researchers developed two computational tools to decode how cells communicate in tissues. sCCIgen creates realistic virtual ...

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.

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) ...

Biological systems are inherently three-dimensional—tissues form intricate layers, networks, and architectures where cells interact in ways that extend far beyond a flat plane. To capture the true ...

The field of cancer immunology has witnessed dramatic progress with the advent of immunotherapies targeting the tumor immune microenvironment (TIME).

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

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 ...

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 ...