Fei Chen and Chenlei Hu at the Broad Institute of MIT and Harvard have developed a new imaging-free spatial transcriptomics technology that tracks the diffusion of DNA barcodes between beads in an ...

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.

Applying single-cell RNA sequencing has led researchers to be able to profile the entire transcriptome of cells. However, these transcriptomes prove difficult to link back to their original location ...

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Advancements to include CosMx® Whole Transcriptome Panel; enhanced technology engine to power CellScape™ for spatial proteomics; expansion to 1000-plex protein assay on GeoMx® DSP; and launch of ...

ImSpiRE enhances spatial resolution in three steps: it first extracts image features from spots and patches based on histological images, then computes the relationships between spots and patches, and ...

The field of spatial transcriptomics utilizes technologies that map gene expression data to specific cellular locations within tissues. While traditional RNA sequencing methods generate quantitative ...

The Whole Transcriptome Panel for Bruker’s CosMx Spatial Molecular Imager (SMI) represents a breakthrough in spatial biology. With the ability to detect and quantify over 18,000 RNA transcripts at ...

Spatial omics is transforming how researchers understand tissue biology, revealing the complex interplay between cells in health and disease. While RNA expression studies provide important molecular ...

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