Spatial transcriptomics (ST) has revolutionized biomedical research by enabling scientists to measure gene expression while ...

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.

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 ...

(MEMPHIS, Tenn. – December 3, 2025) 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 ...

Knowing the location of a gene within intact tissue or a single cell allows scientists to unlock unknown cellular functions. This information is often lost in most genetic sequencing techniques, but ...

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 ...

Race-specific survival prediction models for de novo metastatic breast cancer using machine learning. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not ...

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 ...

Jasmine Plummer shares the spatial omics techniques she has developed to investigate the cellular processes underlying disease.