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 ...

Constructed image from spatial transcriptomics slides measuring gene expression in tissues. This shows the developing upper limb, including the developing hand and digits. Each spot represents a ...

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 ...

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 ...

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 ...