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data analysis spatial transcriptomic experiment  (10X Genomics)

 
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    10X Genomics data analysis spatial transcriptomic experiment
    Data Analysis Spatial Transcriptomic Experiment, 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/kriging/pm42226209-88-10-38
    Average 86 stars, based on 1 article reviews
    data analysis spatial transcriptomic experiment - by Bioz Stars, 2026-09
    86/100 stars

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    Spatial Transcriptomics:

    Article Title: Transcriptomic profiling of the ovarian immune landscape reveals distinct macrophage subsets and activation of the NLRP3 inflammasome likely contributing to accelerated follicular atresia in classic galactosemia.
    Article Snippet: .. AR TIC LE IN PR ES S Spatial Transcriptomics and data analysis Spatial transcriptomic experiment: Visium ST experiment was performed on the same CG and control patient ovarian tissue samples used for snRNAseq as per the manufacturer’s protocol (10x Genomics). ..

    Control:

    Article Title: Transcriptomic profiling of the ovarian immune landscape reveals distinct macrophage subsets and activation of the NLRP3 inflammasome likely contributing to accelerated follicular atresia in classic galactosemia.
    Article Snippet: .. AR TIC LE IN PR ES S Spatial Transcriptomics and data analysis Spatial transcriptomic experiment: Visium ST experiment was performed on the same CG and control patient ovarian tissue samples used for snRNAseq as per the manufacturer’s protocol (10x Genomics). ..



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    The workflow of the improved tensor completion algorithm under the C2F framework. The interpolated data in this figure are generated from the soil heavy metal dataset, which was created using the ordinary <t>Kriging</t> <t>interpolation</t> method with ESRI ArcGIS 10.8 software ( https://www.esri.com ).
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    The workflow of the improved tensor completion algorithm under the C2F framework. The interpolated data in this figure are generated from the soil heavy metal dataset, which was created using the ordinary Kriging interpolation method with ESRI ArcGIS 10.8 software ( https://www.esri.com ).

    Journal: Scientific Reports

    Article Title: A prediction model for soil heavy metal content based on improved tensor completion

    doi: 10.1038/s41598-025-07565-7

    Figure Lengend Snippet: The workflow of the improved tensor completion algorithm under the C2F framework. The interpolated data in this figure are generated from the soil heavy metal dataset, which was created using the ordinary Kriging interpolation method with ESRI ArcGIS 10.8 software ( https://www.esri.com ).

    Article Snippet: The interpolated data in this figure are generated from the soil heavy metal dataset, which was created using the ordinary Kriging interpolation method with ESRI ArcGIS 10.8 software ( https://www.esri.com ).

    Techniques: Generated, Software

    Kriging interpolation results for different metals. The interpolation results in this figure are generated from the soil heavy metal dataset, which was created using the ordinary Kriging interpolation method with ESRI ArcGIS 10.8 software ( https://www.esri.com ).

    Journal: Scientific Reports

    Article Title: A prediction model for soil heavy metal content based on improved tensor completion

    doi: 10.1038/s41598-025-07565-7

    Figure Lengend Snippet: Kriging interpolation results for different metals. The interpolation results in this figure are generated from the soil heavy metal dataset, which was created using the ordinary Kriging interpolation method with ESRI ArcGIS 10.8 software ( https://www.esri.com ).

    Article Snippet: The interpolated data in this figure are generated from the soil heavy metal dataset, which was created using the ordinary Kriging interpolation method with ESRI ArcGIS 10.8 software ( https://www.esri.com ).

    Techniques: Generated, Software

    As completion process. The original heatmap in Fig. 3 are generated from the soil heavy metal dataset, which was created using the ordinary Kriging interpolation method with ESRI ArcGIS 10.8 software ( https://www.esri.com ).

    Journal: Scientific Reports

    Article Title: A prediction model for soil heavy metal content based on improved tensor completion

    doi: 10.1038/s41598-025-07565-7

    Figure Lengend Snippet: As completion process. The original heatmap in Fig. 3 are generated from the soil heavy metal dataset, which was created using the ordinary Kriging interpolation method with ESRI ArcGIS 10.8 software ( https://www.esri.com ).

    Article Snippet: The interpolated data in this figure are generated from the soil heavy metal dataset, which was created using the ordinary Kriging interpolation method with ESRI ArcGIS 10.8 software ( https://www.esri.com ).

    Techniques: Generated, Software