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 ...

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.

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 ...

Race-specific survival prediction models for de novo metastatic breast cancer using machine learning. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not ...

The partners are launching ImmuneScape, a multiomics program using spatial and single-cell sequencing to study immune drivers ...

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 ...

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) ...

Exploring biology in its native environment is perhaps the ideal scenario for generating better hypotheses about the cellular interactions that influence—and drive—healthy and diseased states, ...

Researchers developed two computational tools to decode how cells communicate in tissues. sCCIgen creates realistic virtual ...