The rapid development of spatial transcriptomics (ST) technologies has greatly advanced the understanding of gene expression, tissue architecture, cellular composition, and disease mechanisms within ...

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.

A wave of spatial transcriptomics studies has produced gene-expression atlases that span entire organs and whole organisms, ...

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 ...

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 ...

Multi-omics refers to an integrated approach that combines data from multiple "omics" technologies to provide a holistic ...

In the rapidly developing field of spatial biology, researchers are working to expand our understanding of biological processes within their spatial context. Scientists are taking a holistic approach ...

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 ...

Researchers reveal the intricate molecular landscape of triple-negative breast cancer (TNBC), uncovering actionable spatial archetypes and gene signatures that pave the way for personalized therapies ...

Rare cancers encompass a heterogeneous group of malignancies characterized by low incidence and prevalence but, often, disproportionately high mortality ...