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spatial transcriptomics sequencing st seq  (Spatial Transcriptomics Inc)

 
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    Spatial Transcriptomics Inc spatial transcriptomics sequencing st seq
    Spatial Transcriptomics Sequencing St Seq, supplied by Spatial Transcriptomics Inc, 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/spatial+transcriptomics+sequencing+(st-seq)/seq+st/pmc12356410-227-0-0
    Average 86 stars, based on 1 article reviews
    spatial transcriptomics sequencing st seq - by Bioz Stars, 2026-10
    86/100 stars

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    Related Articles

    Spatial Transcriptomics:

    Article Title: AEBP1 drives fibroblast-mediated T cell dysfunction in tumors.
    Article Snippet: Subsequent to cell quantification, the samples were processed and sequenced on the Illumina NovaSeq 6000 platform in San Diego, California, following the manufacturer’s protocol. .. Spatial transcriptomics data analysis The stRNA-seq slides of two human COAD samples were printed with two identical capture regions. ..

    Article Title: Integrating multi-modal transcriptomics identifies cellular subtypes with distinct roles in PDAC progression.
    Article Snippet: .. Spatial transcriptomics (ST-seq) data, including the HTANPDAC and GEO datasets GSE233293 and GSE202740, totaling 20 ST-seq samples, were jointly analyzed via the R packages Seurat and BayesSpace in R4.1.1 [41]. ..

    Article Title: Single-cell multi-omics in cancer immunotherapy: from tumor heterogeneity to personalized precision treatment
    Article Snippet: Spatial Transcriptomics , 2016 , corrFISH , Single-cell , [ ] . .. Spatial Transcriptomics , 2017 , Geo-seq , Single-cell , [ ] . .. Spatial Transcriptomics , 2018 , Visium , 55 μm , [ ] .

    Article Title: Single-cell multi-omics in cancer immunotherapy: from tumor heterogeneity to personalized precision treatment
    Article Snippet: Spatial Transcriptomics , 2019 , HDST , 2 μm , [ ] . .. Spatial Transcriptomics + Proteomics , 2020 , DBiT-seq , 10–50 μm , [ ] . .. Spatial Transcriptomics + Proteomics , 2020 , GeoMx DSP , Single-cell , [ ] .

    Article Title: Biology-driven insights into the power of single-cell foundation models
    Article Snippet: .. scGPT [ ] , scRNA-seq, scATAC-seq, CITE-seq, spatial transcriptomics , 50 M , 33 M , 1200 HVGs , 512 , Value binning , Lookup Table (512d) , × , Encoder with attention mask , Iterative MGM with MSE loss (gene-prompt + cell-prompt), generative pretraining. .. UCE [ ] , scRNA-Seq , 650 M , 36 M , 1024 non-unique genes sampled (with replacement) by expression and ordered by genomic positions , 1280 , / , ESM-2 [ ] based protein embedding (5120d) , ✓ , Encoder , Modified MGM: binary CE loss for predicting whether a gene is expressed or not.

    Gene Expression:

    Article Title: Application of transcriptomics techniques in skin cancer
    Article Snippet: Single-cell RNA sequencing technology (scRNA-seq) , Gene expression profiles in single cell samples , Gene expression abundance and cell type , 1. Revealing cellular heterogeneity. 2. Building cell atlases. 3. Inferring differentiation trajectories. 4. Resolving the cellular composition of complex tissues. , 1. Loss of original spatial location information. 2. Dissociation process may result in the loss of specific cells. 3. High cost. 4. Complex data analysis.. .. Spatial Transcriptomics (ST-seq) , Organization of gene expression profiles retaining spatial location information , Gene expression abundance, cell type and spatial location information , 1. Preserve and interpret the spatial context of gene expression. 2. Locate specific gene types within tissues. 3. Study tissue microenvironments and link molecular phenotypes to tissue morphology. , 1. Data analysis is more complex and requires the integration of images and multi-omics. 2. The cost of technology is extremely high. 3. The number of genes covered may be limited.. .. MM , RNA-seq , MITF, AXL , BRAF/MEK, anti-PD-1 antibody , ( ) .

    Biomarker Discovery:

    Article Title: Application of transcriptomics techniques in skin cancer
    Article Snippet: Single-cell RNA sequencing technology (scRNA-seq) , Gene expression profiles in single cell samples , Gene expression abundance and cell type , 1. Revealing cellular heterogeneity. 2. Building cell atlases. 3. Inferring differentiation trajectories. 4. Resolving the cellular composition of complex tissues. , 1. Loss of original spatial location information. 2. Dissociation process may result in the loss of specific cells. 3. High cost. 4. Complex data analysis.. .. Spatial Transcriptomics (ST-seq) , Organization of gene expression profiles retaining spatial location information , Gene expression abundance, cell type and spatial location information , 1. Preserve and interpret the spatial context of gene expression. 2. Locate specific gene types within tissues. 3. Study tissue microenvironments and link molecular phenotypes to tissue morphology. , 1. Data analysis is more complex and requires the integration of images and multi-omics. 2. The cost of technology is extremely high. 3. The number of genes covered may be limited.. .. MM , RNA-seq , MITF, AXL , BRAF/MEK, anti-PD-1 antibody , ( ) .

    Sequencing:

    Article Title: Biomaterial-mediated Cell Atlas: an insight from single-cell and spatial transcriptomics
    Article Snippet: .. Spatial transcriptomics sequencing (ST-seq) enables the identification of distinct cell populations while preserving their spatial context, offering essential insights into cell function, phenotype, and positional relationships within the tissue microenvironment [ , ]. ..

    Preserving:

    Article Title: Biomaterial-mediated Cell Atlas: an insight from single-cell and spatial transcriptomics
    Article Snippet: .. Spatial transcriptomics sequencing (ST-seq) enables the identification of distinct cell populations while preserving their spatial context, offering essential insights into cell function, phenotype, and positional relationships within the tissue microenvironment [ , ]. ..

    Cell Function Assay:

    Article Title: Biomaterial-mediated Cell Atlas: an insight from single-cell and spatial transcriptomics
    Article Snippet: .. Spatial transcriptomics sequencing (ST-seq) enables the identification of distinct cell populations while preserving their spatial context, offering essential insights into cell function, phenotype, and positional relationships within the tissue microenvironment [ , ]. ..

    Single Cell:

    Article Title: Single-cell multi-omics in cancer immunotherapy: from tumor heterogeneity to personalized precision treatment
    Article Snippet: Spatial Transcriptomics , 2016 , corrFISH , Single-cell , [ ] . .. Spatial Transcriptomics , 2017 , Geo-seq , Single-cell , [ ] . .. Spatial Transcriptomics , 2018 , Visium , 55 μm , [ ] .



    Similar Products

    spatial transcriptomics sequencing st seq  (Spatial Transcriptomics Inc)
    86
    Spatial Transcriptomics Inc spatial transcriptomics sequencing st seq
    Spatial Transcriptomics Sequencing St Seq, supplied by Spatial Transcriptomics Inc, 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/spatial+transcriptomics+sequencing+(st-seq)/seq+st/pmc12356410-227-0-0
    Average 86 stars, based on 1 article reviews
    spatial transcriptomics sequencing st seq - by Bioz Stars, 2026-10
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    spatial transcriptomics sequencing st-seq  (Spatial Transcriptomics Inc)
    90
    Spatial Transcriptomics Inc spatial transcriptomics sequencing st-seq
    Spatial Transcriptomics Sequencing St Seq, 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/spatial+transcriptomics+sequencing+(st-seq)/spatial+transcriptomics++st+/pmc12160929-266-0-0
    Average 90 stars, based on 1 article reviews
    spatial transcriptomics sequencing st-seq - by Bioz Stars, 2026-10
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    spatial transcriptome sequencing (st-seq) dataset  (Mendeley Ltd)
    90
    Mendeley Ltd spatial transcriptome sequencing (st-seq) dataset
    Transcription programs of ccRCC cells in response to cuproptosis. A UMAP showing the 10 subtypes of 26,981 Epithelial cells; B heatmap showing inferred CNV of scRNA-seq dataset; C dot plot of the relative cellular proportions of Epithelial subtypes in each group; D GSEA analysis revealed the activated CRGs enriched in Normal Epithelial cells; E violin plot showing the relative CRGs score in each cancer subtype; F survival plot of HILPDA + ccRCC1 signature high and low group in the KIRC samples; G violin plots of HILPDA expression levels and hypoxia scores in each cancer subtypes; H spatial <t>transcriptome</t> displayed the distribution of CRGs, HILPDA + ccRCC1 signatures, hypoxia scores and HILPDA expression; I the regulon specificity scores of TFs in HILPDA + ccRCC1 subtype. The top 5 TFs ordered by scores were listed; J violin plot showing the expression levels of the top 5 TFs in HILPDA + ccRCC1 subtype across stage I–IV.
    Spatial Transcriptome Sequencing (St Seq) Dataset, supplied by Mendeley Ltd, 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/spatial+transcriptomics+sequencing+(st-seq)/spatial+transcriptomic+data/pmc11266328-46-1-9
    Average 90 stars, based on 1 article reviews
    spatial transcriptome sequencing (st-seq) dataset - by Bioz Stars, 2026-10
    90/100 stars
    		  Buy from Supplier
    spatial transcriptomics sequencing (st-seq)  (Spatial Transcriptomics Inc)
    90
    Spatial Transcriptomics Inc spatial transcriptomics sequencing (st-seq)
    Transcription programs of ccRCC cells in response to cuproptosis. A UMAP showing the 10 subtypes of 26,981 Epithelial cells; B heatmap showing inferred CNV of scRNA-seq dataset; C dot plot of the relative cellular proportions of Epithelial subtypes in each group; D GSEA analysis revealed the activated CRGs enriched in Normal Epithelial cells; E violin plot showing the relative CRGs score in each cancer subtype; F survival plot of HILPDA + ccRCC1 signature high and low group in the KIRC samples; G violin plots of HILPDA expression levels and hypoxia scores in each cancer subtypes; H spatial <t>transcriptome</t> displayed the distribution of CRGs, HILPDA + ccRCC1 signatures, hypoxia scores and HILPDA expression; I the regulon specificity scores of TFs in HILPDA + ccRCC1 subtype. The top 5 TFs ordered by scores were listed; J violin plot showing the expression levels of the top 5 TFs in HILPDA + ccRCC1 subtype across stage I–IV.
    Spatial Transcriptomics Sequencing (St Seq), 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/spatial+transcriptomics+sequencing+(st-seq)/spatial+transcriptomics+sequencing/pmc10942862-252-4-2
    Average 90 stars, based on 1 article reviews
    spatial transcriptomics sequencing (st-seq) - by Bioz Stars, 2026-10
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    Transcription programs of ccRCC cells in response to cuproptosis. A UMAP showing the 10 subtypes of 26,981 Epithelial cells; B heatmap showing inferred CNV of scRNA-seq dataset; C dot plot of the relative cellular proportions of Epithelial subtypes in each group; D GSEA analysis revealed the activated CRGs enriched in Normal Epithelial cells; E violin plot showing the relative CRGs score in each cancer subtype; F survival plot of HILPDA + ccRCC1 signature high and low group in the KIRC samples; G violin plots of HILPDA expression levels and hypoxia scores in each cancer subtypes; H spatial transcriptome displayed the distribution of CRGs, HILPDA + ccRCC1 signatures, hypoxia scores and HILPDA expression; I the regulon specificity scores of TFs in HILPDA + ccRCC1 subtype. The top 5 TFs ordered by scores were listed; J violin plot showing the expression levels of the top 5 TFs in HILPDA + ccRCC1 subtype across stage I–IV.

    Journal: Discover Oncology

    Article Title: Characterization of cuproptosis signature in clear cell renal cell carcinoma by single cell and spatial transcriptome analysis

    doi: 10.1007/s12672-024-01162-2

    Figure Lengend Snippet: Transcription programs of ccRCC cells in response to cuproptosis. A UMAP showing the 10 subtypes of 26,981 Epithelial cells; B heatmap showing inferred CNV of scRNA-seq dataset; C dot plot of the relative cellular proportions of Epithelial subtypes in each group; D GSEA analysis revealed the activated CRGs enriched in Normal Epithelial cells; E violin plot showing the relative CRGs score in each cancer subtype; F survival plot of HILPDA + ccRCC1 signature high and low group in the KIRC samples; G violin plots of HILPDA expression levels and hypoxia scores in each cancer subtypes; H spatial transcriptome displayed the distribution of CRGs, HILPDA + ccRCC1 signatures, hypoxia scores and HILPDA expression; I the regulon specificity scores of TFs in HILPDA + ccRCC1 subtype. The top 5 TFs ordered by scores were listed; J violin plot showing the expression levels of the top 5 TFs in HILPDA + ccRCC1 subtype across stage I–IV.

    Article Snippet: The spatial transcriptome sequencing (ST-seq) dataset was obtained from Mendeley Data platform ( https://data.mendeley.com/datasets/g67bkbnhhg/1 ) and input to python environment.

    Techniques: Expressing

    Dissection of immunosuppressive cells of cuproptosis-related tumor microenvironment. A UMAP showing the 16 subtypes of 99,210 Immune cells; B violin plot of the relative expression levels of the canocial markers in each subtype; C heatmap showing the enrichment of immune checkpoint and suppressive genes; D spatial transcriptome displayed the distribution of Treg, CD8_Exhausted and TAM signature scores; E heatmap showing the four gene expression patterns deduced by TDEseq analysis; F violin plots showing the relative expression levels of CRG scores in the immunosuppressive cells across different stages; G Chord diagram showing the number of interactions among the four subtypes; H Bubble plot showing the ligand-receptor pairs in the main subtype; I Heatmap showing the relative expression levels of key genes of the four subtypes among the different stages. The paired ligand-receptor shown in H were connected by lines.

    Journal: Discover Oncology

    Article Title: Characterization of cuproptosis signature in clear cell renal cell carcinoma by single cell and spatial transcriptome analysis

    doi: 10.1007/s12672-024-01162-2

    Figure Lengend Snippet: Dissection of immunosuppressive cells of cuproptosis-related tumor microenvironment. A UMAP showing the 16 subtypes of 99,210 Immune cells; B violin plot of the relative expression levels of the canocial markers in each subtype; C heatmap showing the enrichment of immune checkpoint and suppressive genes; D spatial transcriptome displayed the distribution of Treg, CD8_Exhausted and TAM signature scores; E heatmap showing the four gene expression patterns deduced by TDEseq analysis; F violin plots showing the relative expression levels of CRG scores in the immunosuppressive cells across different stages; G Chord diagram showing the number of interactions among the four subtypes; H Bubble plot showing the ligand-receptor pairs in the main subtype; I Heatmap showing the relative expression levels of key genes of the four subtypes among the different stages. The paired ligand-receptor shown in H were connected by lines.

    Article Snippet: The spatial transcriptome sequencing (ST-seq) dataset was obtained from Mendeley Data platform ( https://data.mendeley.com/datasets/g67bkbnhhg/1 ) and input to python environment.

    Techniques: Dissection, Expressing, Gene Expression