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

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

Abstract: Spatial transcriptomics (ST) clustering identifies distinct spatial domains within tissues and elucidates cellular interactions. While this approach has advanced human understanding of ...

The global initiative aims to profile up to 100,000 patient specimens to scale M-Optimus, the world model of biology, representing a ~20x increase in scale over existing data available in the world ...

Hepatocellular carcinoma (HCC) is a highly heterogeneous malignancy characterized by marked cellular and spatial diversity within the tumor microenvironment (TME). The transforming growth factor-β ...

Inflammatory bowel disease (IBD), comprising ulcerative colitis (UC) and Crohn’s disease (CD), represents a diagnostic challenge owing to its overlapping clinical features. Precise molecular ...

Abstract: Spatial transcriptomics (ST) aims to decode spatially resolved gene expression patterns while preserving tissue morphology. Current methods tend to use lower-cost deep learning approaches ...