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 ...
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.
Researchers at the John Innes Center and the Earlham Institute are pioneering powerful single-cell visualization techniques ...
Spatial transcriptomics is a technique that provides information about gene expression patterns within intact tissues. This technology employs various methodologies, including in situ sequencing (ISS) ...
Researchers developed two computational tools to decode how cells communicate in tissues. sCCIgen creates realistic virtual ...
We combine advanced technologies such as spatial transcriptomics, multiplexed imaging, and in situ sequencing to map cellular components in their native tissue context. Obtain high-resolution data ...
Spatial ribonucleic acid (RNA) transcriptomics measures gene expression while preserving each molecule’s coordinates in intact tissue, tying transcripts to histology and local microenvironments.
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 ...
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 ...
Technological development is key to improving the way hematologic cancer is diagnosed and treated. With this vision, the Josep Carreras Leukemia Research Institute is committed to the creation and ...
Strapped with an extra APP, people with Down’s syndrome are all but destined to develop Alzheimer’s dementia if they live past middle age. Compared with sporadic forms of the disease, DSAD starts ...