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.

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

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 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 ...

Fei Chen and Chenlei Hu at the Broad Institute of MIT and Harvard have developed a new imaging-free spatial transcriptomics technology that tracks the diffusion of DNA barcodes between beads in an ...

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 ...

Knowing the location of a gene within intact tissue or a single cell allows scientists to unlock unknown cellular functions. This information is often lost in most genetic sequencing techniques, but ...

Technological development is key to improving the way hematologic cancer is diagnosed and treated. With this vision, the Josep Carreras Leukemia Research Institute is committed to the creation and ...