Spatial transcriptomics is revolutionizing the study of tissue architecture, cellular states, and tumor-immune interactions in clinical specimens. This presentation introduces the principles and ...

In this session you will learn how spatial transcriptomics with single-cell resolution enable detailed cellular mapping of ...

Spatial-biology tools are collecting more comprehensive data, and companies that want to model cells in silico are hoovering ...

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

Applying single-cell RNA sequencing has led researchers to be able to profile the entire transcriptome of cells. However, these transcriptomes prove difficult to link back to their original location ...

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 ...

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 ...

Spatial biology is a rapidly advancing discipline that examines biological molecules (such as DNA, RNA, and proteins) within their native locations in tissues. This approach offers critical insight ...

Spatial transcriptomics is transforming how scientists see biology—literally—by mapping gene activity in its original location inside tissues. From decoding tumor architecture to charting entire ...

Enhancing a low-cost, minimally invasive screening test for dihydropyrimidine dehydrogenase mutations linked to 5-fluorouracil sensitivity by integrating computational mutation predictions. This is an ...