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 ...

Scientists at Duke-NUS Medical School have developed two powerful computational tools that could transform how researchers ...

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 ...

In a recent study published in the journal Nature, researchers developed spatial aging clocks using single-cell transcriptomics to explore cell-type-specific interactions and their impact on brain ...

Certain cells in the brain create a nurturing environment, enhancing the health and resilience of their neighbors, while others promote stress and damage. Using spatial transcriptomics and AI, ...

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 provides a unique perspective on the genes that cells express and where those cells are located. However, the rapid growth of the technology has come at the cost of ...

This article explores how researchers are using spatially resolved methods to explore diverse biological processes from ...

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 ...

Researchers developed a microfluidic method to isolate glioblastoma-derived extracellular vesicles from blood. By leveraging ...