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 ...

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

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 ...

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.

Tumors contain many different types of cells organized in complex spatial patterns that can influence how the disease ...

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 ...

Researchers developed an analytic framework for spatial-omics data that can help to map biological activity within tumors.

Andreas Pfenning discusses the techniques being developed and used to study neuronal heterogeneity and the therapeutic potential of his work.

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 ...