Spatial transcriptomics (ST) technologies reveal the spatial organization of gene expression in tissues, providing critical insights into development, neurobiology, and cancer. However, the high cost ...

Why do so many promising drugs fail? This article explores how spatial multiomics reveals hidden cell interactions, helping ...

Capturing spatial information is essential to elucidate how cells function and interact within their native tissue environment. However, the initial spatial transcriptomics techniques have several ...

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 ...

This illustration summarizes how integrated spatial transcriptomics, single-cell transcriptomics, single-cell epigenomics, and spatial epigenomics enable multi-dimensional profiling of the tumor ...

Master Scaling Single-Cell Biology. This free webinar series covers multi-omic data integration, spatial datasets, and new AI models.

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 ...

Researchers at The University of Texas MD Anderson Cancer Center have developed a spatial map of muscle-invasive bladder ...

Bulk RNA sequencing has advanced transcriptomic analysis across diverse biological systems, but averaging gene expression across cell populations can obscure important cellular differences.