A metabolic enzyme found in the support cells surrounding tumors may hold the key to predicting which cancer patients will ...

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

Rare cancers encompass a heterogeneous group of malignancies characterized by low incidence and prevalence but, often, disproportionately high mortality ...

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

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 ...

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

Prostate cancer affects one in five Australian men, making it the most common cancer in the country. Now, researchers at the ...

This Research Topic is the second volume of the “Unraveling Breast Cancer Complexity: Insights from Single-Cell Sequencing and Spatial Transcriptomics” ...

Integration of Takara Bio USA’s Trekker® reagent kit with Illumina’s Single Cell 3′ RNA Prep assay delivers high-density, high-sensitivity spatial data with true single-cell resolution SAN JOSE, Calif ...

Portfolio innovations include the launch of the new CellScape XR spatial proteomics platform, the unique CosMx mouse whole transcriptome panel, the launch of the PaintScape platform for 3D genome ...

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

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 ...