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.

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

The field of spatial transcriptomics utilizes technologies that map gene expression data to specific cellular locations within tissues. While traditional RNA sequencing methods generate quantitative ...

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 ...

Illumina has announced the development of an advanced spatial transcriptomics technology, with commercial availability expected in 2026. This next-generation solution is designed to enhance ...

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 ...