Spatial transcriptomics now spans two fundamentally different measurement strategies, and the choice between them shapes every downstream result a lab will generate. Sequencing-based platforms capture ...
A Nature Methods benchmark of 11 segmentation methods across 15 spatial transcriptomics datasets shows that algorithm and ...
Spatial biology captures molecular complexity by preserving the physical context of cells in their native environments. From deciphering RNA dynamics within stress granules to scaling molecular ...
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 ...
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 ...
New simulator and computational tools generate realistic ‘virtual tissues’ and map cell-to-cell ‘conversations’ from spatial transcriptomics data, potentially accelerating AI-driven discoveries in ...
Scientists first reported a method to locate RNA within tissue samples in the late 1960s, using in situ hybridization (ISH) to fix cells within their spatial context, label specific RNA molecules with ...
Spatial biology is a rapidly advancing discipline that examines biological molecules (such as DNA, RNA, and proteins) within their native locations in tissues. This approach offers critical insight ...
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