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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: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/spatial+transcriptomics+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, 2026-09
90/100 stars

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Related Articles

Gene Expression:

Article Title: STHD: probabilistic cell typing of single spots in whole transcriptome spatial data with high definition
Article Snippet: Spatial transcriptomics (ST) technologies have enabled gene expression profiling in the native spatial context of tissues.

Article Title: An integrated single-cell reference atlas of the human endometrium
Article Snippet: To annotate the epithelial cell states present in the human endometrium we considered: (i) the distinctive expression of genes, including bona fide markers (Fig. 2a & Fig. 3a), (ii) the menstrual stage at which these cells appear (Fig. 1f), and (iii) their spatial coordinates, as inferred by integrating single-cell transcriptomics with Spatial Transcriptomics (Visium) (Fig. 2b-f and Extended Data Fig. 7).

Article Title: Integrating spatial transcriptomics and snRNA-seq data enhances differential gene expression analysis results of AD-related phenotypes
Article Snippet: Spatial transcriptomics (ST) technologies have revolutionized the understanding of spatially informed gene expression, which provide invaluable insights into the molecular architecture of complex diseases such as Alzheimer disease (AD).

Article Title: An integrated single-cell reference atlas of the human endometrium
Article Snippet: To annotate the stromal cell states present in the human endometrium, we used the same approach described in Supplementary Note 3 for the annotation of epithelial cells which considered: (i) the distinctive expression of genes, including bona fide markers (Fig. 3a), (ii) the menstrual stage at which these cells appear (Fig. 1f), and (iii) their spatial coordinates, as inferred by integrating single-cell transcriptomics with Spatial Transcriptomics (Visium) (Fig. 3b).

Article Title: Bering: joint cell segmentation and annotation for spatial transcriptomics with transferred graph embeddings
Article Snippet: Additionally, the size of features in image-based spatial transcriptomics technologies has increased from 30 to 10,000 , making it increasingly feasible to use deep learning models.

Article Title: Centrosome-, mitotic spindle- and cytokinetic bridge-specific compartmentalization of AGO2 protein in human liver cells undergoing mitosis: Non-canonical, RNAi-dependent, control of local homeostasis
Article Snippet: Spatial transcriptomics-mediated profiling of the mRNA/siRNA species populating either TRBP2 +/+ or TRBP2 −/− MEF-residing centrosomes in dividing/mitotic vs. interphase cells may indicate TRBP2-independent centrosome-specific RNAi machinery that functions non-canonically during mitosis.

Article Title:
Article Snippet: B266/P1991 Imaging-based spatial transcriptomics technology identifies predictive biomarkers for relapse in colon cancer stage II.

Article Title: Integrating spatial transcriptomics and snRNA-seq data enhances differential gene expression analysis results of AD-related phenotypes
Article Snippet: Spatial transcriptomics (ST) data provide spatially informed gene expression profiles.

Histopathology:

Article Title: STHD: probabilistic cell typing of single spots in whole transcriptome spatial data with high definition
Article Snippet: Spatial transcriptomics (ST) technologies have enabled gene expression profiling in the native spatial context of tissues.

Article Title: An integrated single-cell reference atlas of the human endometrium
Article Snippet: To annotate the epithelial cell states present in the human endometrium we considered: (i) the distinctive expression of genes, including bona fide markers (Fig. 2a & Fig. 3a), (ii) the menstrual stage at which these cells appear (Fig. 1f), and (iii) their spatial coordinates, as inferred by integrating single-cell transcriptomics with Spatial Transcriptomics (Visium) (Fig. 2b-f and Extended Data Fig. 7).

Article Title: Integrating spatial transcriptomics and snRNA-seq data enhances differential gene expression analysis results of AD-related phenotypes
Article Snippet: Spatial transcriptomics (ST) technologies have revolutionized the understanding of spatially informed gene expression, which provide invaluable insights into the molecular architecture of complex diseases such as Alzheimer disease (AD).

Article Title: An integrated single-cell reference atlas of the human endometrium
Article Snippet: To annotate the stromal cell states present in the human endometrium, we used the same approach described in Supplementary Note 3 for the annotation of epithelial cells which considered: (i) the distinctive expression of genes, including bona fide markers (Fig. 3a), (ii) the menstrual stage at which these cells appear (Fig. 1f), and (iii) their spatial coordinates, as inferred by integrating single-cell transcriptomics with Spatial Transcriptomics (Visium) (Fig. 3b).

Article Title: Bering: joint cell segmentation and annotation for spatial transcriptomics with transferred graph embeddings
Article Snippet: Additionally, the size of features in image-based spatial transcriptomics technologies has increased from 30 to 10,000 , making it increasingly feasible to use deep learning models.

Article Title: Centrosome-, mitotic spindle- and cytokinetic bridge-specific compartmentalization of AGO2 protein in human liver cells undergoing mitosis: Non-canonical, RNAi-dependent, control of local homeostasis
Article Snippet: Spatial transcriptomics-mediated profiling of the mRNA/siRNA species populating either TRBP2 +/+ or TRBP2 −/− MEF-residing centrosomes in dividing/mitotic vs. interphase cells may indicate TRBP2-independent centrosome-specific RNAi machinery that functions non-canonically during mitosis.

Article Title:
Article Snippet: B266/P1991 Imaging-based spatial transcriptomics technology identifies predictive biomarkers for relapse in colon cancer stage II.

Article Title: Integrating spatial transcriptomics and snRNA-seq data enhances differential gene expression analysis results of AD-related phenotypes
Article Snippet: Spatial transcriptomics (ST) data provide spatially informed gene expression profiles.

Comparison:

Article Title: STHD: probabilistic cell typing of single spots in whole transcriptome spatial data with high definition
Article Snippet: Spatial transcriptomics (ST) technologies have enabled gene expression profiling in the native spatial context of tissues.

Article Title: An integrated single-cell reference atlas of the human endometrium
Article Snippet: To annotate the epithelial cell states present in the human endometrium we considered: (i) the distinctive expression of genes, including bona fide markers (Fig. 2a & Fig. 3a), (ii) the menstrual stage at which these cells appear (Fig. 1f), and (iii) their spatial coordinates, as inferred by integrating single-cell transcriptomics with Spatial Transcriptomics (Visium) (Fig. 2b-f and Extended Data Fig. 7).

Article Title: Integrating spatial transcriptomics and snRNA-seq data enhances differential gene expression analysis results of AD-related phenotypes
Article Snippet: Spatial transcriptomics (ST) technologies have revolutionized the understanding of spatially informed gene expression, which provide invaluable insights into the molecular architecture of complex diseases such as Alzheimer disease (AD).

Article Title: An integrated single-cell reference atlas of the human endometrium
Article Snippet: To annotate the stromal cell states present in the human endometrium, we used the same approach described in Supplementary Note 3 for the annotation of epithelial cells which considered: (i) the distinctive expression of genes, including bona fide markers (Fig. 3a), (ii) the menstrual stage at which these cells appear (Fig. 1f), and (iii) their spatial coordinates, as inferred by integrating single-cell transcriptomics with Spatial Transcriptomics (Visium) (Fig. 3b).

Article Title: Bering: joint cell segmentation and annotation for spatial transcriptomics with transferred graph embeddings
Article Snippet: Additionally, the size of features in image-based spatial transcriptomics technologies has increased from 30 to 10,000 , making it increasingly feasible to use deep learning models.

Article Title: Centrosome-, mitotic spindle- and cytokinetic bridge-specific compartmentalization of AGO2 protein in human liver cells undergoing mitosis: Non-canonical, RNAi-dependent, control of local homeostasis
Article Snippet: Spatial transcriptomics-mediated profiling of the mRNA/siRNA species populating either TRBP2 +/+ or TRBP2 −/− MEF-residing centrosomes in dividing/mitotic vs. interphase cells may indicate TRBP2-independent centrosome-specific RNAi machinery that functions non-canonically during mitosis.

Article Title:
Article Snippet: B266/P1991 Imaging-based spatial transcriptomics technology identifies predictive biomarkers for relapse in colon cancer stage II.

Article Title: Integrating spatial transcriptomics and snRNA-seq data enhances differential gene expression analysis results of AD-related phenotypes
Article Snippet: Spatial transcriptomics (ST) data provide spatially informed gene expression profiles.

Expressing:

Article Title: STHD: probabilistic cell typing of single spots in whole transcriptome spatial data with high definition
Article Snippet: Spatial transcriptomics (ST) technologies have enabled gene expression profiling in the native spatial context of tissues.

Article Title: An integrated single-cell reference atlas of the human endometrium
Article Snippet: To annotate the epithelial cell states present in the human endometrium we considered: (i) the distinctive expression of genes, including bona fide markers (Fig. 2a & Fig. 3a), (ii) the menstrual stage at which these cells appear (Fig. 1f), and (iii) their spatial coordinates, as inferred by integrating single-cell transcriptomics with Spatial Transcriptomics (Visium) (Fig. 2b-f and Extended Data Fig. 7).

Article Title: Integrating spatial transcriptomics and snRNA-seq data enhances differential gene expression analysis results of AD-related phenotypes
Article Snippet: Spatial transcriptomics (ST) technologies have revolutionized the understanding of spatially informed gene expression, which provide invaluable insights into the molecular architecture of complex diseases such as Alzheimer disease (AD).

Article Title: An integrated single-cell reference atlas of the human endometrium
Article Snippet: To annotate the stromal cell states present in the human endometrium, we used the same approach described in Supplementary Note 3 for the annotation of epithelial cells which considered: (i) the distinctive expression of genes, including bona fide markers (Fig. 3a), (ii) the menstrual stage at which these cells appear (Fig. 1f), and (iii) their spatial coordinates, as inferred by integrating single-cell transcriptomics with Spatial Transcriptomics (Visium) (Fig. 3b).

Article Title: Bering: joint cell segmentation and annotation for spatial transcriptomics with transferred graph embeddings
Article Snippet: Additionally, the size of features in image-based spatial transcriptomics technologies has increased from 30 to 10,000 , making it increasingly feasible to use deep learning models.

Article Title: Centrosome-, mitotic spindle- and cytokinetic bridge-specific compartmentalization of AGO2 protein in human liver cells undergoing mitosis: Non-canonical, RNAi-dependent, control of local homeostasis
Article Snippet: Spatial transcriptomics-mediated profiling of the mRNA/siRNA species populating either TRBP2 +/+ or TRBP2 −/− MEF-residing centrosomes in dividing/mitotic vs. interphase cells may indicate TRBP2-independent centrosome-specific RNAi machinery that functions non-canonically during mitosis.

Article Title:
Article Snippet: B266/P1991 Imaging-based spatial transcriptomics technology identifies predictive biomarkers for relapse in colon cancer stage II.

Article Title: Integrating spatial transcriptomics and snRNA-seq data enhances differential gene expression analysis results of AD-related phenotypes
Article Snippet: Spatial transcriptomics (ST) data provide spatially informed gene expression profiles.

Marker:

Article Title: STHD: probabilistic cell typing of single spots in whole transcriptome spatial data with high definition
Article Snippet: Spatial transcriptomics (ST) technologies have enabled gene expression profiling in the native spatial context of tissues.

Article Title: An integrated single-cell reference atlas of the human endometrium
Article Snippet: To annotate the epithelial cell states present in the human endometrium we considered: (i) the distinctive expression of genes, including bona fide markers (Fig. 2a & Fig. 3a), (ii) the menstrual stage at which these cells appear (Fig. 1f), and (iii) their spatial coordinates, as inferred by integrating single-cell transcriptomics with Spatial Transcriptomics (Visium) (Fig. 2b-f and Extended Data Fig. 7).

Article Title: Integrating spatial transcriptomics and snRNA-seq data enhances differential gene expression analysis results of AD-related phenotypes
Article Snippet: Spatial transcriptomics (ST) technologies have revolutionized the understanding of spatially informed gene expression, which provide invaluable insights into the molecular architecture of complex diseases such as Alzheimer disease (AD).

Article Title: An integrated single-cell reference atlas of the human endometrium
Article Snippet: To annotate the stromal cell states present in the human endometrium, we used the same approach described in Supplementary Note 3 for the annotation of epithelial cells which considered: (i) the distinctive expression of genes, including bona fide markers (Fig. 3a), (ii) the menstrual stage at which these cells appear (Fig. 1f), and (iii) their spatial coordinates, as inferred by integrating single-cell transcriptomics with Spatial Transcriptomics (Visium) (Fig. 3b).

Article Title: Bering: joint cell segmentation and annotation for spatial transcriptomics with transferred graph embeddings
Article Snippet: Additionally, the size of features in image-based spatial transcriptomics technologies has increased from 30 to 10,000 , making it increasingly feasible to use deep learning models.

Article Title: Centrosome-, mitotic spindle- and cytokinetic bridge-specific compartmentalization of AGO2 protein in human liver cells undergoing mitosis: Non-canonical, RNAi-dependent, control of local homeostasis
Article Snippet: Spatial transcriptomics-mediated profiling of the mRNA/siRNA species populating either TRBP2 +/+ or TRBP2 −/− MEF-residing centrosomes in dividing/mitotic vs. interphase cells may indicate TRBP2-independent centrosome-specific RNAi machinery that functions non-canonically during mitosis.

Article Title:
Article Snippet: B266/P1991 Imaging-based spatial transcriptomics technology identifies predictive biomarkers for relapse in colon cancer stage II.

Article Title: Integrating spatial transcriptomics and snRNA-seq data enhances differential gene expression analysis results of AD-related phenotypes
Article Snippet: Spatial transcriptomics (ST) data provide spatially informed gene expression profiles.

Single-cell Transcriptomics:

Article Title: STHD: probabilistic cell typing of single spots in whole transcriptome spatial data with high definition
Article Snippet: Spatial transcriptomics (ST) technologies have enabled gene expression profiling in the native spatial context of tissues.

Article Title: An integrated single-cell reference atlas of the human endometrium
Article Snippet: To annotate the epithelial cell states present in the human endometrium we considered: (i) the distinctive expression of genes, including bona fide markers (Fig. 2a & Fig. 3a), (ii) the menstrual stage at which these cells appear (Fig. 1f), and (iii) their spatial coordinates, as inferred by integrating single-cell transcriptomics with Spatial Transcriptomics (Visium) (Fig. 2b-f and Extended Data Fig. 7).

Article Title: Integrating spatial transcriptomics and snRNA-seq data enhances differential gene expression analysis results of AD-related phenotypes
Article Snippet: Spatial transcriptomics (ST) technologies have revolutionized the understanding of spatially informed gene expression, which provide invaluable insights into the molecular architecture of complex diseases such as Alzheimer disease (AD).

Article Title: An integrated single-cell reference atlas of the human endometrium
Article Snippet: To annotate the stromal cell states present in the human endometrium, we used the same approach described in Supplementary Note 3 for the annotation of epithelial cells which considered: (i) the distinctive expression of genes, including bona fide markers (Fig. 3a), (ii) the menstrual stage at which these cells appear (Fig. 1f), and (iii) their spatial coordinates, as inferred by integrating single-cell transcriptomics with Spatial Transcriptomics (Visium) (Fig. 3b).

Article Title: Bering: joint cell segmentation and annotation for spatial transcriptomics with transferred graph embeddings
Article Snippet: Additionally, the size of features in image-based spatial transcriptomics technologies has increased from 30 to 10,000 , making it increasingly feasible to use deep learning models.

Article Title: Centrosome-, mitotic spindle- and cytokinetic bridge-specific compartmentalization of AGO2 protein in human liver cells undergoing mitosis: Non-canonical, RNAi-dependent, control of local homeostasis
Article Snippet: Spatial transcriptomics-mediated profiling of the mRNA/siRNA species populating either TRBP2 +/+ or TRBP2 −/− MEF-residing centrosomes in dividing/mitotic vs. interphase cells may indicate TRBP2-independent centrosome-specific RNAi machinery that functions non-canonically during mitosis.

Article Title:
Article Snippet: B266/P1991 Imaging-based spatial transcriptomics technology identifies predictive biomarkers for relapse in colon cancer stage II.

Article Title: Integrating spatial transcriptomics and snRNA-seq data enhances differential gene expression analysis results of AD-related phenotypes
Article Snippet: Spatial transcriptomics (ST) data provide spatially informed gene expression profiles.



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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.
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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.
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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.
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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