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interactive multiomics data visualization platform  (Complete Genomics Inc)


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    Complete Genomics Inc interactive multiomics data visualization platform
    Interactive Multiomics Data Visualization Platform, supplied by Complete Genomics Inc, used in various techniques. Bioz Stars score: 99/100, based on 484 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/transcriptomic+data+set/Stereo-seq+Transcriptomics+Set+for+FFPE/pm41410774-218-4-10
    Average 99 stars, based on 484 article reviews
    interactive multiomics data visualization platform - by Bioz Stars, 2026-10
    99/100 stars

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    Related Articles

    Spatial Transcriptomics:

    Article Title: A pan cancer multi omics analysis of OLR1 reveals its association with tumor immunity metabolic pathways and clinical prognosis
    Article Snippet: .. Spatial transcriptomics datasets were obtained from the STOmics database (https://db.cngb.org/stomics/) and the GEO database (https://www.ncbi.nlm.nih.gov/geo/), including STDS0000027, STDS0000033, STDS0000046, GSM5924031, and GSM6505133. ..

    Article Title: Spi1-Soat1 Transcriptional axis drives microglial lipid droplet accumulation and secondary brain injury after intracerebral hemorrhage
    Article Snippet: .. Cholesterol metabolic pathway activation and microglia-specific upregulation of Soat1 are tightly associated with lipid droplet accumulation after ICH To define the core metabolic pathways and key regulators driving microglial LD accumulation after ICH, we analyzed the day 7 perihematomal tissue subset of a spatial transcriptomics dataset (STOmics DB, ID:STT0000047), with a focus on lipid metabolic cascades underlying LD biogenesis (Fig. 3A). ..

    Analysis:

    Article Title: Diverse infections transcriptionally reprogram the intestinal epithelium and epithelial-immune cell interactions.
    Article Snippet: .. Indeed, using Stereo-seq (STOmics) spatial transcriptomic analysis, which profiles host and microbial RNA, we found that Yersinia transcripts were localized to the basal region of the PG and did not extend to the enterocytes overlaying the PG (Supplementary Fig. 10g). ..

    Sequencing:

    Article Title: Multi-omics integration and machine learning identify an ACKR1 + endothelial cell-based lactate-immune signature associated with carotid plaque vulnerability and progression.
    Article Snippet: .. The internal singlecell and spatial transcriptomes were deposited with our previous study (Lai et al., Nat Cardiovasc Res, 2025) in the Genome Sequence Archive for Human at the National Genomics Data Center under accession HRA006030 (https://ngdc.cncb.ac.cn/gsa-human), with backups in the China National GeneBank: spatial transcriptomes in the STOmics Database (STT0000052, https://db.cngb.org/stomics/) and single-cell data in the China National Sequence Archive (CNP0004894, https:// db.cngb.org/cnsa/). ..

    Single Cell:

    Article Title: Multi-omics integration and machine learning identify an ACKR1 + endothelial cell-based lactate-immune signature associated with carotid plaque vulnerability and progression.
    Article Snippet: .. The internal singlecell and spatial transcriptomes were deposited with our previous study (Lai et al., Nat Cardiovasc Res, 2025) in the Genome Sequence Archive for Human at the National Genomics Data Center under accession HRA006030 (https://ngdc.cncb.ac.cn/gsa-human), with backups in the China National GeneBank: spatial transcriptomes in the STOmics Database (STT0000052, https://db.cngb.org/stomics/) and single-cell data in the China National Sequence Archive (CNP0004894, https:// db.cngb.org/cnsa/). ..

    Activation Assay:

    Article Title: Spi1-Soat1 Transcriptional axis drives microglial lipid droplet accumulation and secondary brain injury after intracerebral hemorrhage
    Article Snippet: .. Cholesterol metabolic pathway activation and microglia-specific upregulation of Soat1 are tightly associated with lipid droplet accumulation after ICH To define the core metabolic pathways and key regulators driving microglial LD accumulation after ICH, we analyzed the day 7 perihematomal tissue subset of a spatial transcriptomics dataset (STOmics DB, ID:STT0000047), with a focus on lipid metabolic cascades underlying LD biogenesis (Fig. 3A). ..

    Tissue:

    Article Title: Spi1-Soat1 Transcriptional axis drives microglial lipid droplet accumulation and secondary brain injury after intracerebral hemorrhage
    Article Snippet: .. Cholesterol metabolic pathway activation and microglia-specific upregulation of Soat1 are tightly associated with lipid droplet accumulation after ICH To define the core metabolic pathways and key regulators driving microglial LD accumulation after ICH, we analyzed the day 7 perihematomal tissue subset of a spatial transcriptomics dataset (STOmics DB, ID:STT0000047), with a focus on lipid metabolic cascades underlying LD biogenesis (Fig. 3A). ..

    H&E Stain:

    Article Title: Spatial transcriptomic profiling of porcine tissue microarray detecting subclinical circovirus infection
    Article Snippet: .. The first section was subjected to H&E staining for histological evaluation, while the second was mounted directly onto a Stereo-seq chip N Slide V1.0 (STOmics, Cat. No. 210CN114). .. Subsequent processing was performed according to the Stereo-seq Transcriptomics Set for FFPE User Manual (Document No. STUM-TT004) using the Stereo-seq Transcriptomics N Kit V1.0 (Cat. No. 211KN114) and Stereo-seq 16 Barcode Library Preparation Kit V1.0 (Cat. No. 111KL160).



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    Single-nucleus transcriptome and spatial <t>transcriptomics</t> landscape of the ileal tissue of SAP and CON group rats. (A) Schematic illustration of the workflow for this study. (B) Representative Hematoxylin and Eosin (H&E)–stained ileal sections from CON and SAP rats. (C) UMAP plot of single-nucleus transcriptome profiles of SAP and CON group samples. Colors indicate groups, clusters and cell types. (D) Heatmap plot of marker genes for cell annotation. (E) Bar plot showing cell-type proportions (mean ± SEM) in snRNA-seq data. (F) Spatial transcriptomics profiles of SAP and CON group samples. Colors indicate cell types. (G) Bar plot showing cell-type proportions (mean ± SEM) in spatial transcriptomics (Stereo-seq) data. Statistical significance: ns, not significant; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.
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    Single-nucleus transcriptome and spatial <t>transcriptomics</t> landscape of the ileal tissue of SAP and CON group rats. (A) Schematic illustration of the workflow for this study. (B) Representative Hematoxylin and Eosin (H&E)–stained ileal sections from CON and SAP rats. (C) UMAP plot of single-nucleus transcriptome profiles of SAP and CON group samples. Colors indicate groups, clusters and cell types. (D) Heatmap plot of marker genes for cell annotation. (E) Bar plot showing cell-type proportions (mean ± SEM) in snRNA-seq data. (F) Spatial transcriptomics profiles of SAP and CON group samples. Colors indicate cell types. (G) Bar plot showing cell-type proportions (mean ± SEM) in spatial transcriptomics (Stereo-seq) data. Statistical significance: ns, not significant; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.
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    Image Search Results


    Single-nucleus transcriptome and spatial transcriptomics landscape of the ileal tissue of SAP and CON group rats. (A) Schematic illustration of the workflow for this study. (B) Representative Hematoxylin and Eosin (H&E)–stained ileal sections from CON and SAP rats. (C) UMAP plot of single-nucleus transcriptome profiles of SAP and CON group samples. Colors indicate groups, clusters and cell types. (D) Heatmap plot of marker genes for cell annotation. (E) Bar plot showing cell-type proportions (mean ± SEM) in snRNA-seq data. (F) Spatial transcriptomics profiles of SAP and CON group samples. Colors indicate cell types. (G) Bar plot showing cell-type proportions (mean ± SEM) in spatial transcriptomics (Stereo-seq) data. Statistical significance: ns, not significant; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.

    Journal: Frontiers in Immunology

    Article Title: Single-nucleus and spatial transcriptomics reveal intestinal cellular heterogeneity, differentiation, and cell communication mechanisms in SAP-induced intestinal injury

    doi: 10.3389/fimmu.2026.1719902

    Figure Lengend Snippet: Single-nucleus transcriptome and spatial transcriptomics landscape of the ileal tissue of SAP and CON group rats. (A) Schematic illustration of the workflow for this study. (B) Representative Hematoxylin and Eosin (H&E)–stained ileal sections from CON and SAP rats. (C) UMAP plot of single-nucleus transcriptome profiles of SAP and CON group samples. Colors indicate groups, clusters and cell types. (D) Heatmap plot of marker genes for cell annotation. (E) Bar plot showing cell-type proportions (mean ± SEM) in snRNA-seq data. (F) Spatial transcriptomics profiles of SAP and CON group samples. Colors indicate cell types. (G) Bar plot showing cell-type proportions (mean ± SEM) in spatial transcriptomics (Stereo-seq) data. Statistical significance: ns, not significant; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.

    Article Snippet: The spatial transcriptomics data were obtained according to the protocol of STOmics Gene Expression Set-S1 on the website ( https://www.stomics.tech/ ), which is an improved version of initial procedures.

    Techniques: Spatial Transcriptomics, Staining, Marker