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 ...
Foundation models (FMs), which are deep learning models pretrained on large-scale data and applied to diverse downstream tasks, have transformed natural language processing and multimodal AI. However, ...
Spatial transcriptomics is revolutionizing the study of tissue architecture, cellular states, and tumor-immune interactions in clinical specimens. This presentation introduces the principles and ...
Spatial transcriptomics (ST) technologies reveal the spatial organization of gene expression in tissues, providing critical insights into development, neurobiology, and cancer. However, the high cost ...
A wave of spatial transcriptomics studies has produced gene-expression atlases that span entire organs and whole organisms, from mouse embryos to the roundworm C. elegans to 31 human tissues. These ...
Joe Beechem, PhD, joined NanoString in 2012 as the senior vice president of research and development and is now Bruker Spatial Biology chief scientific officer. He is an inventor and full commercial ...
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 ...
Large Language Models in Population Oncology: A Contemporary Review on the Use of Large Language Models to Support Data Collection, Aggregation, and Analysis in Cancer Care and Research Cancer remains ...
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What Is Spatial Transcriptomics?
Spatial transcriptomics is a technique that provides information about gene expression patterns within intact tissues. This technology employs various methodologies, including in situ sequencing (ISS) ...
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