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 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 ...

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 ...

A wave of spatial transcriptomics studies has produced gene-expression atlases that span entire organs and whole organisms, ...

Foundation models (FMs), which are deep learning models pretrained on large-scale data and applied to diverse downstream ...

Neoadjuvant immunotherapy in combination with chemotherapy in resectable locally advanced head and neck squamous cell carcinoma: A randomized, open label, phase II clinical trial. This is an ASCO ...

A team of researchers has constructed the most detailed single-cell map of the adult human prostate to date, cataloging more ...

Tumors contain many different types of cells organized in complex spatial patterns that can influence how the disease progresses. Because of this, it is hard to predict how a tumor will develop and ...

Researchers developed a new computational method to analyze complex tissue data that could transform our current understanding of diseases and how we treat them. Researchers at the University of ...

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 ...