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 ...

A team of Vanderbilt researchers has released a new benchmarking study that aims to assist scientists in selecting the most effective methods for analyzing spatial transcriptomics (ST) data. ST ...

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 ...

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

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 ...

People communicate with each other, sometimes face to face, sometimes with a text message or phone call. Cells also ...

Illumina, Inc. (NASDAQ: ILMN) today announced the launch of the StrataMap Spatial Solution, offering an unmatched breadth of ...

The Transplant Company™, a leading precision medicine company focused on the discovery, development, and commercialization of clinically differentiated, high‑value healthcare solutions for transplant ...

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