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.

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 ...

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) ...

Illumina is raising the curtain on its upcoming entry into spatial transcriptomics, with tech designed to help researchers explore cellular behavior mapped across complex tissues. The announcement ...

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 ...

Spatial transcriptomics provides a unique perspective on the genes that cells express and where those cells are located. However, the rapid growth of the technology has come at the cost of ...

Single-cell RNA transcriptomics allows researchers to broadly profile the gene expression of individual cells in a particular tissue. This technique has allowed researchers to identify new subsets of ...

Biological systems are inherently three-dimensional—tissues form intricate layers, networks, and architectures where cells interact in ways that extend far beyond a flat plane. To capture the true ...

Spatial biology is reshaping how researchers study cancer by revealing the architecture and complexity of tumors in extraordinary detail. Through techniques that combine protein- and gene-level ...

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 ...