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 ...

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 ...

In a recent study published in Nature, researchers investigate the spatial organization of cancer cells and the tumor microenvironment by analyzing over one hundred tumor sections across six types of ...

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 ...

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 ...

PALO ALTO, Calif.--(BUSINESS WIRE)--Curio Bioscience today announced it has commenced commercial operations with the launch of Curio Seeker, the world’s first high-resolution, whole-transcriptome ...

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 ...

This eBook cuts through the complexity of spatial techniques, featuring a series of interviews with pioneers in the field, and peer-reviewed research from the Taylor & Francis journal portfolio. This ...

“Illumina’s…presentations and product descriptions revealed a workflow that infringed on the ‘607, ‘138, ‘505, and ‘487 patents, 10x Genomics and Prognosys Biosciences argued.” On October 21, 10x ...

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.