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mcd files  (MathWorks Inc)


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    MathWorks Inc mcd files
    Mcd Files, supplied by MathWorks 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/result/mcd files/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    mcd files - by Bioz Stars, 2026-03
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    Spatial molecular profiling of mouse corneas infected with GFP-McKrae using IMC. Mice were ocularly infected with 2 × 10 5 PFU/eye of GFP-McKrae virus as described in and the Materials and Methods without corneal scarification. Uninfected mice were used as controls. Whole eyes were harvested on days 3 and 5 PI and sectioned. Regions-of-interest (ROIs) were assigned to different corneal regions, and samples were ablated on <t>a</t> <t>Hyperion</t> imaging system (Standard Biotools). Each antibody produced a single image per sample, which was collectively used to construct a multi-image stack in <t>MCD</t> format. Cell segmentation, feature extraction, and normalization were performed. Cell populations were identified using iterative PhenoGraph clustering. Final matrix data were converted to .FCS files within the MATLAB pipeline for clustering and heatmap creation. Panels: ( A–D ) uninfected cornea, ( E–H ) day 3 PI, and ( I–L ) day 5 PI. (A, E, and I): ROIs were combined as single-cell stacked images depicting single-cell map of mouse cornea. (B, F, and J): Heatmaps show expression of structural (aSMA, and E-cadherin), immune cell markers (B220, CD11b, CD11c, CD163, CD3, CD4, CD45, CD68, CD8a, F4/80, Ly-6G, iNOS, and FoxP3), and GFP in assigned cell clusters. Expression was non-log normalized, ranging from 0 to 1. (C, G, and K): Expression/distribution of GFP in assigned cell clusters as a violin plot, ranging from 0 to 1. (D, H, and L): Heatmap of neighbor analysis using HISTOCAT to determine nearest cell neighbor to each start point cell to investigate. These positive, neutral, and negative interactions were then collated to create the overall proportion heatmap for the condition (region, etc.) ranging from 1 (100% of images showed positive interaction) to −1 (100% of images showed negative interaction).
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    Spatial molecular profiling of mouse corneas infected with GFP-McKrae using IMC. Mice were ocularly infected with 2 × 10 5 PFU/eye of GFP-McKrae virus as described in and the Materials and Methods without corneal scarification. Uninfected mice were used as controls. Whole eyes were harvested on days 3 and 5 PI and sectioned. Regions-of-interest (ROIs) were assigned to different corneal regions, and samples were ablated on <t>a</t> <t>Hyperion</t> imaging system (Standard Biotools). Each antibody produced a single image per sample, which was collectively used to construct a multi-image stack in <t>MCD</t> format. Cell segmentation, feature extraction, and normalization were performed. Cell populations were identified using iterative PhenoGraph clustering. Final matrix data were converted to .FCS files within the MATLAB pipeline for clustering and heatmap creation. Panels: ( A–D ) uninfected cornea, ( E–H ) day 3 PI, and ( I–L ) day 5 PI. (A, E, and I): ROIs were combined as single-cell stacked images depicting single-cell map of mouse cornea. (B, F, and J): Heatmaps show expression of structural (aSMA, and E-cadherin), immune cell markers (B220, CD11b, CD11c, CD163, CD3, CD4, CD45, CD68, CD8a, F4/80, Ly-6G, iNOS, and FoxP3), and GFP in assigned cell clusters. Expression was non-log normalized, ranging from 0 to 1. (C, G, and K): Expression/distribution of GFP in assigned cell clusters as a violin plot, ranging from 0 to 1. (D, H, and L): Heatmap of neighbor analysis using HISTOCAT to determine nearest cell neighbor to each start point cell to investigate. These positive, neutral, and negative interactions were then collated to create the overall proportion heatmap for the condition (region, etc.) ranging from 1 (100% of images showed positive interaction) to −1 (100% of images showed negative interaction).
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    Spatial molecular profiling of mouse corneas infected with GFP-McKrae using IMC. Mice were ocularly infected with 2 × 10 5 PFU/eye of GFP-McKrae virus as described in and the Materials and Methods without corneal scarification. Uninfected mice were used as controls. Whole eyes were harvested on days 3 and 5 PI and sectioned. Regions-of-interest (ROIs) were assigned to different corneal regions, and samples were ablated on <t>a</t> <t>Hyperion</t> imaging system (Standard Biotools). Each antibody produced a single image per sample, which was collectively used to construct a multi-image stack in <t>MCD</t> format. Cell segmentation, feature extraction, and normalization were performed. Cell populations were identified using iterative PhenoGraph clustering. Final matrix data were converted to .FCS files within the MATLAB pipeline for clustering and heatmap creation. Panels: ( A–D ) uninfected cornea, ( E–H ) day 3 PI, and ( I–L ) day 5 PI. (A, E, and I): ROIs were combined as single-cell stacked images depicting single-cell map of mouse cornea. (B, F, and J): Heatmaps show expression of structural (aSMA, and E-cadherin), immune cell markers (B220, CD11b, CD11c, CD163, CD3, CD4, CD45, CD68, CD8a, F4/80, Ly-6G, iNOS, and FoxP3), and GFP in assigned cell clusters. Expression was non-log normalized, ranging from 0 to 1. (C, G, and K): Expression/distribution of GFP in assigned cell clusters as a violin plot, ranging from 0 to 1. (D, H, and L): Heatmap of neighbor analysis using HISTOCAT to determine nearest cell neighbor to each start point cell to investigate. These positive, neutral, and negative interactions were then collated to create the overall proportion heatmap for the condition (region, etc.) ranging from 1 (100% of images showed positive interaction) to −1 (100% of images showed negative interaction).
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    Spatial molecular profiling of mouse corneas infected with GFP-McKrae using IMC. Mice were ocularly infected with 2 × 10 5 PFU/eye of GFP-McKrae virus as described in and the Materials and Methods without corneal scarification. Uninfected mice were used as controls. Whole eyes were harvested on days 3 and 5 PI and sectioned. Regions-of-interest (ROIs) were assigned to different corneal regions, and samples were ablated on <t>a</t> <t>Hyperion</t> imaging system (Standard Biotools). Each antibody produced a single image per sample, which was collectively used to construct a multi-image stack in <t>MCD</t> format. Cell segmentation, feature extraction, and normalization were performed. Cell populations were identified using iterative PhenoGraph clustering. Final matrix data were converted to .FCS files within the MATLAB pipeline for clustering and heatmap creation. Panels: ( A–D ) uninfected cornea, ( E–H ) day 3 PI, and ( I–L ) day 5 PI. (A, E, and I): ROIs were combined as single-cell stacked images depicting single-cell map of mouse cornea. (B, F, and J): Heatmaps show expression of structural (aSMA, and E-cadherin), immune cell markers (B220, CD11b, CD11c, CD163, CD3, CD4, CD45, CD68, CD8a, F4/80, Ly-6G, iNOS, and FoxP3), and GFP in assigned cell clusters. Expression was non-log normalized, ranging from 0 to 1. (C, G, and K): Expression/distribution of GFP in assigned cell clusters as a violin plot, ranging from 0 to 1. (D, H, and L): Heatmap of neighbor analysis using HISTOCAT to determine nearest cell neighbor to each start point cell to investigate. These positive, neutral, and negative interactions were then collated to create the overall proportion heatmap for the condition (region, etc.) ranging from 1 (100% of images showed positive interaction) to −1 (100% of images showed negative interaction).
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    Spatial molecular profiling of mouse corneas infected with GFP-McKrae using IMC. Mice were ocularly infected with 2 × 10 5 PFU/eye of GFP-McKrae virus as described in and the Materials and Methods without corneal scarification. Uninfected mice were used as controls. Whole eyes were harvested on days 3 and 5 PI and sectioned. Regions-of-interest (ROIs) were assigned to different corneal regions, and samples were ablated on <t>a</t> <t>Hyperion</t> imaging system (Standard Biotools). Each antibody produced a single image per sample, which was collectively used to construct a multi-image stack in <t>MCD</t> format. Cell segmentation, feature extraction, and normalization were performed. Cell populations were identified using iterative PhenoGraph clustering. Final matrix data were converted to .FCS files within the MATLAB pipeline for clustering and heatmap creation. Panels: ( A–D ) uninfected cornea, ( E–H ) day 3 PI, and ( I–L ) day 5 PI. (A, E, and I): ROIs were combined as single-cell stacked images depicting single-cell map of mouse cornea. (B, F, and J): Heatmaps show expression of structural (aSMA, and E-cadherin), immune cell markers (B220, CD11b, CD11c, CD163, CD3, CD4, CD45, CD68, CD8a, F4/80, Ly-6G, iNOS, and FoxP3), and GFP in assigned cell clusters. Expression was non-log normalized, ranging from 0 to 1. (C, G, and K): Expression/distribution of GFP in assigned cell clusters as a violin plot, ranging from 0 to 1. (D, H, and L): Heatmap of neighbor analysis using HISTOCAT to determine nearest cell neighbor to each start point cell to investigate. These positive, neutral, and negative interactions were then collated to create the overall proportion heatmap for the condition (region, etc.) ranging from 1 (100% of images showed positive interaction) to −1 (100% of images showed negative interaction).
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    Image Search Results


    Spatial molecular profiling of mouse corneas infected with GFP-McKrae using IMC. Mice were ocularly infected with 2 × 10 5 PFU/eye of GFP-McKrae virus as described in and the Materials and Methods without corneal scarification. Uninfected mice were used as controls. Whole eyes were harvested on days 3 and 5 PI and sectioned. Regions-of-interest (ROIs) were assigned to different corneal regions, and samples were ablated on a Hyperion imaging system (Standard Biotools). Each antibody produced a single image per sample, which was collectively used to construct a multi-image stack in MCD format. Cell segmentation, feature extraction, and normalization were performed. Cell populations were identified using iterative PhenoGraph clustering. Final matrix data were converted to .FCS files within the MATLAB pipeline for clustering and heatmap creation. Panels: ( A–D ) uninfected cornea, ( E–H ) day 3 PI, and ( I–L ) day 5 PI. (A, E, and I): ROIs were combined as single-cell stacked images depicting single-cell map of mouse cornea. (B, F, and J): Heatmaps show expression of structural (aSMA, and E-cadherin), immune cell markers (B220, CD11b, CD11c, CD163, CD3, CD4, CD45, CD68, CD8a, F4/80, Ly-6G, iNOS, and FoxP3), and GFP in assigned cell clusters. Expression was non-log normalized, ranging from 0 to 1. (C, G, and K): Expression/distribution of GFP in assigned cell clusters as a violin plot, ranging from 0 to 1. (D, H, and L): Heatmap of neighbor analysis using HISTOCAT to determine nearest cell neighbor to each start point cell to investigate. These positive, neutral, and negative interactions were then collated to create the overall proportion heatmap for the condition (region, etc.) ranging from 1 (100% of images showed positive interaction) to −1 (100% of images showed negative interaction).

    Journal: mBio

    Article Title: A novel GFP-based strategy to quantitate cellular spatial associations in HSV-1 viral pathogenesis

    doi: 10.1128/mbio.01454-24

    Figure Lengend Snippet: Spatial molecular profiling of mouse corneas infected with GFP-McKrae using IMC. Mice were ocularly infected with 2 × 10 5 PFU/eye of GFP-McKrae virus as described in and the Materials and Methods without corneal scarification. Uninfected mice were used as controls. Whole eyes were harvested on days 3 and 5 PI and sectioned. Regions-of-interest (ROIs) were assigned to different corneal regions, and samples were ablated on a Hyperion imaging system (Standard Biotools). Each antibody produced a single image per sample, which was collectively used to construct a multi-image stack in MCD format. Cell segmentation, feature extraction, and normalization were performed. Cell populations were identified using iterative PhenoGraph clustering. Final matrix data were converted to .FCS files within the MATLAB pipeline for clustering and heatmap creation. Panels: ( A–D ) uninfected cornea, ( E–H ) day 3 PI, and ( I–L ) day 5 PI. (A, E, and I): ROIs were combined as single-cell stacked images depicting single-cell map of mouse cornea. (B, F, and J): Heatmaps show expression of structural (aSMA, and E-cadherin), immune cell markers (B220, CD11b, CD11c, CD163, CD3, CD4, CD45, CD68, CD8a, F4/80, Ly-6G, iNOS, and FoxP3), and GFP in assigned cell clusters. Expression was non-log normalized, ranging from 0 to 1. (C, G, and K): Expression/distribution of GFP in assigned cell clusters as a violin plot, ranging from 0 to 1. (D, H, and L): Heatmap of neighbor analysis using HISTOCAT to determine nearest cell neighbor to each start point cell to investigate. These positive, neutral, and negative interactions were then collated to create the overall proportion heatmap for the condition (region, etc.) ranging from 1 (100% of images showed positive interaction) to −1 (100% of images showed negative interaction).

    Article Snippet: Ablation sessions from the Fluidigm Hyperion imaging system produce MCD files that contain individual TXT ROI files for each acquisition.

    Techniques: Infection, Virus, Imaging, Produced, Construct, Extraction, Expressing