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 (ST) emerges as a pivotal technique for cataloging gene expression across tissue sections while retaining crucial locational data. Traditional methodologies, encompassing bulk ...

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 ...

New simulator and computational tools generate realistic ‘virtual tissues’ and map cell-to-cell ‘conversations’ from spatial transcriptomics data, potentially accelerating AI-driven discoveries in ...

Spatial transcriptomics is a cutting-edge technique that characterizes gene expression within sections of tissue, such as heart, skin or liver tissue. These snapshots provide insights into how spatial ...