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mouse hippocampus 10x visium hd data set  (10X Genomics)

 
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    10X Genomics mouse hippocampus 10x visium hd data set
    Mouse Hippocampus 10x Visium Hd Data Set, supplied by 10X Genomics, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/10x+visium+data/hd+visium/pm42309667-339-1-12
    Average 86 stars, based on 1 article reviews
    mouse hippocampus 10x visium hd data set - by Bioz Stars, 2026-10
    86/100 stars

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    other:

    Article Title: A composite scaling network of EfficientNet for improving spatial domain identification performance.
    Article Snippet: The three 10x Visium data sets includes the human Dorsolateral Prefrontal Cortex (DLPFC) (http://research.libd.org/spatialLIBD/), the human breast cancer, the mouse brain sagittal anterior and CytAssist fresh frozen mouse brain (https://www.10xgenomics.com/).

    Article Title: Bridging cell morphological behaviors and molecular dynamics in multi-modal spatial omics with MorphLink.
    Article Snippet: 10xgenomics.com/datasets/visium-cytassist-mouse-embryo-11-mmcapture-area-ffpe-2-standard); (8) human breast tumor H&E images from TCGA data (https://portal.gdc.cancer.gov/ sample ID: DX1.01FB49CC, DX1.392580F3, DX1.0E26C46D).

    Article Title: Spatially aligned graph transfer learning for characterizing spatial regulatory heterogeneity
    Article Snippet: The mouse brain coronal 10x Visium data can be downloaded from the 10x Genomics official website at https://www.10xgenomics.com/resources/datasets/ .

    Olfactory:

    Article Title: aKNNO: single-cell and spatial transcriptomics clustering with an optimized adaptive k-nearest neighbor graph
    Article Snippet: .. The 10x Visium data for mouse coronal and sagittal posterior brain [ ] and main olfactory bulb are downloaded from the 10x Genomics website ( https://www.10xgenomics.com/resources/datasets ). ..



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    Image Search Results


    a . A Xenium ST data from human breast carcinoma with single-cell level gene expression of 313 genes in 167,780 cells and an H&E image. Standard NMF is applied to derive a single-cell level embedding as the silver standard high-resolution embedding in the simulation. b . Generation of spots and spot-level gene expression. Spots of radius r are first generated based on a 10x Visium-style mesh grid, and spot-level gene expression is generated by summing cell expressions within spots. A proportion ρ of the spots are randomly excluded to increase the spatial sparsity. c . Error bar plots of MAEs between the silver standard and inferred embedding intensities at the pixel-wise level when varying the exclusion rate and radius of spots with n = 30 (replicates). Error bars: mean ± SD. d . Left panel: a tumour-associated embedding dimension in the single-cell level silver standard. Right panel: Zoomed-in views of three ROIs in the left panel. e . Zoomed-in views of the inferred embedding dimensions by different methods from a simulation dataset (spot radius: 30 pixels) in the ROIs under whole-spots and spots-masking scenarios. The whole-spots scenario means that expressions of all spots of the simulation dataset are used for embedding learning, and the spots-masking scenario means that the ST expressions in the light blue boxes are masked for embedding learning. Scale bars: 200 μm.

    Journal: Nature Cell Biology

    Article Title: The interpretable multimodal dimension reduction framework SpaHDmap enhances resolution in spatial transcriptomics

    doi: 10.1038/s41556-025-01838-z

    Figure Lengend Snippet: a . A Xenium ST data from human breast carcinoma with single-cell level gene expression of 313 genes in 167,780 cells and an H&E image. Standard NMF is applied to derive a single-cell level embedding as the silver standard high-resolution embedding in the simulation. b . Generation of spots and spot-level gene expression. Spots of radius r are first generated based on a 10x Visium-style mesh grid, and spot-level gene expression is generated by summing cell expressions within spots. A proportion ρ of the spots are randomly excluded to increase the spatial sparsity. c . Error bar plots of MAEs between the silver standard and inferred embedding intensities at the pixel-wise level when varying the exclusion rate and radius of spots with n = 30 (replicates). Error bars: mean ± SD. d . Left panel: a tumour-associated embedding dimension in the single-cell level silver standard. Right panel: Zoomed-in views of three ROIs in the left panel. e . Zoomed-in views of the inferred embedding dimensions by different methods from a simulation dataset (spot radius: 30 pixels) in the ROIs under whole-spots and spots-masking scenarios. The whole-spots scenario means that expressions of all spots of the simulation dataset are used for embedding learning, and the spots-masking scenario means that the ST expressions in the light blue boxes are masked for embedding learning. Scale bars: 200 μm.

    Article Snippet: 10x Visium mouse posterior brain sagittal section data are available for MPBS-01 at https://www.10xgenomics.com/resources/datasets/mouse-brain-serial-section-1-sagittal-posterior-1-standard-1-1-0 and for MPBS-02 at https://www.10xgenomics.com/resources/datasets/mouse-brain-serial-section-2-sagittal-posterior-1-standard-1-1-0 .

    Techniques: Single Cell, Gene Expression, Generated