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 ...

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

Bioptimus, a global AI company building the world's first world model for biology, today announced the launch of its Spatial ...

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

Conventional transcriptomic techniques have revealed much about gene expression at the population and single-cell level—but they overlook one crucial factor: spatial context. In musculoskeletal ...

Challenges and Prospects. Challenges and prospects faced by spatial transcriptomics itself and its application to the musculoskeletal system. AI Artificial intelligence, FFPE Formalin fixed and ...

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

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.

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

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 ...

Mount Sinai researchers have published the first organ-wide human skin spatial atlas from across the body. It provides an ...