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spatial transcriptomics geomx® platform  (Spatial Transcriptomics Inc)

 
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    Spatial Transcriptomics Inc spatial transcriptomics geomx® platform
    Spatial Transcriptomics Geomx® Platform, supplied by Spatial Transcriptomics Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/geomx+spatial+transcriptomics+platform/geomx/pm40422184-2-7-3
    Average 90 stars, based on 1 article reviews
    spatial transcriptomics geomx® platform - by Bioz Stars, 2026-10
    90/100 stars

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    Related Articles

    Sequencing:

    Article Title: Categorization of 34 computational methods to detect spatially variable genes from spatially resolved transcriptomics data
    Article Snippet: .. In contrast, sequencing-based SRT technologies, such as Spatial Transcriptomics , 10x Visium , Slide-seq , and GeoMx , capture transcriptome-wide gene expression at a lower spatial resolution. ..

    Transcriptome Wide Gene Expression:

    Article Title: Categorization of 34 computational methods to detect spatially variable genes from spatially resolved transcriptomics data
    Article Snippet: .. In contrast, sequencing-based SRT technologies, such as Spatial Transcriptomics , 10x Visium , Slide-seq , and GeoMx , capture transcriptome-wide gene expression at a lower spatial resolution. ..

    other:

    Article Title: Identification of Prognostic Biomarkers of Ovarian High-Grade Serous Carcinoma: A Preliminary Study Using Spatial Transcriptome Analysis and Multispectral Imaging.
    Article Snippet: Here, we used spatial transcriptomics via the GeoMx® platform, alongside multispectral immune cell immunofluorescence (IF), to identify biomarkers associated with disease progression following first-line treatment of high-grade serous carcinoma (HGSC).

    Expressing:

    Article Title: Novel Integration of Spatial and Single-Cell Omics Data Sets Enables Deeper Insights into IPF Pathogenesis.
    Article Snippet: .. In this example, differential analysis extracted up-regulated fibroblast foci-specific genes (n = 50) from GeoMx spatial transcriptomics [17], and the sum expression of the whole gene set was queried as a z-score in PLIN2+ fibroblast cells from scRNA-seq transcriptomics [21]. (B) PCA plotting of gene expression pattern. (C) Venn graph of the up-regulated region-specific gene sets in five histopathological region types: 32 up-regulated region-specific differential genes for control alveoli, 27 for IPF blood vessel, 41 for IPF distant alveoli, 50 for IPF fibroblast foci and 106 for IPF immune infiltrate. (D) Enrichment z-score summary of 30 cell types in five histopathological region types from spatial transcriptomics. ..

    Gene Expression:

    Article Title: Novel Integration of Spatial and Single-Cell Omics Data Sets Enables Deeper Insights into IPF Pathogenesis.
    Article Snippet: .. In this example, differential analysis extracted up-regulated fibroblast foci-specific genes (n = 50) from GeoMx spatial transcriptomics [17], and the sum expression of the whole gene set was queried as a z-score in PLIN2+ fibroblast cells from scRNA-seq transcriptomics [21]. (B) PCA plotting of gene expression pattern. (C) Venn graph of the up-regulated region-specific gene sets in five histopathological region types: 32 up-regulated region-specific differential genes for control alveoli, 27 for IPF blood vessel, 41 for IPF distant alveoli, 50 for IPF fibroblast foci and 106 for IPF immune infiltrate. (D) Enrichment z-score summary of 30 cell types in five histopathological region types from spatial transcriptomics. ..

    Article Title: EACR 2025 Congress: Innovative Cancer Science, 16-19 June 2025.
    Article Snippet: .. Spatial transcriptomics (GeoMx) analyzed gene expression in tumor cells, CAFs, and immune cells. ..

    Control:

    Article Title: Novel Integration of Spatial and Single-Cell Omics Data Sets Enables Deeper Insights into IPF Pathogenesis.
    Article Snippet: .. In this example, differential analysis extracted up-regulated fibroblast foci-specific genes (n = 50) from GeoMx spatial transcriptomics [17], and the sum expression of the whole gene set was queried as a z-score in PLIN2+ fibroblast cells from scRNA-seq transcriptomics [21]. (B) PCA plotting of gene expression pattern. (C) Venn graph of the up-regulated region-specific gene sets in five histopathological region types: 32 up-regulated region-specific differential genes for control alveoli, 27 for IPF blood vessel, 41 for IPF distant alveoli, 50 for IPF fibroblast foci and 106 for IPF immune infiltrate. (D) Enrichment z-score summary of 30 cell types in five histopathological region types from spatial transcriptomics. ..

    Marker:

    Article Title: Interferon-responsive HEVs drive tumor tertiary lymphoid structure formation and predict immunotherapy response in nasopharyngeal carcinoma.
    Article Snippet: .. For marker identification of NPC TLS from GeoMx spatial transcriptomics, differentially expressed genes (NPC TLS versus CN TLS) were filtered with the parameter ‘‘log2 fold change > 0.5 & adjusted P value < 0.05’’. ..

    Spatial Transcriptomics:

    Article Title: EACR 2025 Congress: Innovative Cancer Science, 16-19 June 2025.
    Article Snippet: .. Spatial transcriptomics (GeoMx) analyzed gene expression in tumor cells, CAFs, and immune cells. ..

    Article Title: ROICellTrack: A deep learning framework for integrating cellular imaging modalities in subcellular spatial transcriptomic profiling of tumor tissues.
    Article Snippet: .. Motivation: Spatial transcriptomics (ST) technologies, such as GeoMx Digital Spatial Profiler, are increasingly utilized to investigate the role of diverse tumor microenvironment components, particularly in relation to cancer progression, treatment response, and therapeutic resistance. ..

    Article Title: Interneuron transcriptomics reveals pathologic markers of Alzheimer's disease progression.
    Article Snippet: .. Fig. 1 Spatial transcriptomics of mouse brain and study scheme. (A) Schematic of GeoMx spatial transcriptomics platform for isolating Pv+, Sst+, and VGluT+ regions of interest (ROIs). ..



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    spatial whole transcriptome analysis platform geomx  (Bruker Corporation)
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    Representative H&E images of granulomas from A) Case 3, B) Case 2, and C) Case 4 showing a range of granuloma morphology with D) necrotizing granulomas, E) cellular non-necrotizing granulomas, and F) small, lymphocyte rich granulomas as assessed by a pulmonary pathologist using traditional morphological annotation. Regions of interest (ROIs) ( G-K ) were selected based on morphological and fluorescence staining for DNA (blue), CD3 (green), CD68/CD163 (red), and vimentin (yellow). ROIs bordering necrotic (G) granulomas and (H) solid or cellular granulomas were selected in addition to tertiary lymphoid structures (I), lymph node (J), and uninvolved lung (K) for spatial transcriptional profiling using the human whole <t>transcriptome</t> probe set using GeoMx (Bruker).
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    Image Search Results


    Representative H&E images of granulomas from A) Case 3, B) Case 2, and C) Case 4 showing a range of granuloma morphology with D) necrotizing granulomas, E) cellular non-necrotizing granulomas, and F) small, lymphocyte rich granulomas as assessed by a pulmonary pathologist using traditional morphological annotation. Regions of interest (ROIs) ( G-K ) were selected based on morphological and fluorescence staining for DNA (blue), CD3 (green), CD68/CD163 (red), and vimentin (yellow). ROIs bordering necrotic (G) granulomas and (H) solid or cellular granulomas were selected in addition to tertiary lymphoid structures (I), lymph node (J), and uninvolved lung (K) for spatial transcriptional profiling using the human whole transcriptome probe set using GeoMx (Bruker).

    Journal: bioRxiv

    Article Title: Multiomic analysis identifies suppressive myeloid cell populations in human TB granulomas

    doi: 10.1101/2025.03.10.642376

    Figure Lengend Snippet: Representative H&E images of granulomas from A) Case 3, B) Case 2, and C) Case 4 showing a range of granuloma morphology with D) necrotizing granulomas, E) cellular non-necrotizing granulomas, and F) small, lymphocyte rich granulomas as assessed by a pulmonary pathologist using traditional morphological annotation. Regions of interest (ROIs) ( G-K ) were selected based on morphological and fluorescence staining for DNA (blue), CD3 (green), CD68/CD163 (red), and vimentin (yellow). ROIs bordering necrotic (G) granulomas and (H) solid or cellular granulomas were selected in addition to tertiary lymphoid structures (I), lymph node (J), and uninvolved lung (K) for spatial transcriptional profiling using the human whole transcriptome probe set using GeoMx (Bruker).

    Article Snippet: Due to the limited data on the functional role and significance of MDSCs in TB infected lung tissues, we used an unbiased spatial whole transcriptome analysis (WTA) platform (GeoMx, Bruker, Inc) integrated with single-cell immunophenotyping via highly multiplexed tissue cyclic immunofluorescence (CyCIF) to initiate this study of human TB.

    Techniques: Fluorescence, Staining