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Spatial Transcriptomics Inc spatial transcriptomics st data
Spatial Transcriptomics St Data, 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/transcriptomics+st/data+sequencing+spatial+transcriptomics/pm41610146-199-7-7
Average 86 stars, based on 1 article reviews
spatial transcriptomics st data - by Bioz Stars, 2026-09
86/100 stars

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Related Articles

Expressing:

Article Title: Multiomic analysis of CCNE1 amplification associated molecular and immune features in gynecological cancers
Article Snippet: .. C Spatial transcriptomics ( GSM8207499 ) revealed diffuse CCNE1 expression without distinct clustering, with elevated VEGFB and FBLN2 levels observed in CCNE1-high regions. ..

Spatial Transcriptomics:


Article Title: Multi-omics integration and machine learning define robust molecular subtypes and prognostic signatures in hepatocellular carcinoma.
Article Snippet: .. Single-cell RNA-seq data were obtained from GSE166635 [20] and spatial transcriptomics data (HCC1R and HCC4R) from GSE238264 [21]. ..

Article Title: SpaConTDS: A multimodal contrastive learning framework for identifying spatial domains by applying tuple disturbing strategy
Article Snippet: .. In-depth exploration of the multimodal information within Spatial Transcriptomics (ST) data is essential for understanding the heterogeneity of tissue structure, investigating biological functions and tracking disease progression. ..

Article Title: Single-cell and spatial transcriptomics unveils key regulators governing cell differentiation for Schistosoma sexual development
Article Snippet: .. The sequencing data from Stereo-seq spatial transcriptomics was processed using Stereo-seq Analysis Workflow (SAW) v8.0 ( https://en.stomics.tech ). ..

Article Title: SGMS2+ macrophages enhance NR4A3hi NK cell infiltration to improve prognosis and PD-1 treatment efficacy in hepatocellular carcinoma
Article Snippet: .. Spatial transcriptomics sequencing data were obtained from http://lifeome.net/supp/livercancer-st/data.htm and analyzed using Seurat in R. Subsequently, SCTtransform normalization was performed. ..

Article Title: SpaConTDS: A multimodal contrastive learning framework for identifying spatial domains by applying tuple disturbing strategy.
Article Snippet: .. In-depth exploration of the multimodal information within Spatial Transcriptomics (ST) data is essential for understanding the heterogeneity of tissue structure, investigating biological functions and tracking disease progression. ..

Single Cell:

Article Title: Multi-omics integration and machine learning define robust molecular subtypes and prognostic signatures in hepatocellular carcinoma.
Article Snippet: .. Single-cell RNA-seq data were obtained from GSE166635 [20] and spatial transcriptomics data (HCC1R and HCC4R) from GSE238264 [21]. ..

RNA Sequencing:

Article Title: Multi-omics integration and machine learning define robust molecular subtypes and prognostic signatures in hepatocellular carcinoma.
Article Snippet: .. Single-cell RNA-seq data were obtained from GSE166635 [20] and spatial transcriptomics data (HCC1R and HCC4R) from GSE238264 [21]. ..

Gene Expression:

Article Title: Multiomic analysis of CCNE1 amplification associated molecular and immune features in gynecological cancers
Article Snippet: .. C Spatial transcriptomics ( GSM7019835 ) depicting the gene expression patterns of CCNE1, EPCAM (epithelial marker), and the colocalized genes ARHGAP1 and STK24, which are involved in structural remodeling and cell motility. ..

Marker:

Article Title: Multiomic analysis of CCNE1 amplification associated molecular and immune features in gynecological cancers
Article Snippet: .. C Spatial transcriptomics ( GSM7019835 ) depicting the gene expression patterns of CCNE1, EPCAM (epithelial marker), and the colocalized genes ARHGAP1 and STK24, which are involved in structural remodeling and cell motility. ..

Biomarker Discovery:

Article Title: SpaConTDS: A multimodal contrastive learning framework for identifying spatial domains by applying tuple disturbing strategy
Article Snippet: .. In-depth exploration of the multimodal information within Spatial Transcriptomics (ST) data is essential for understanding the heterogeneity of tissue structure, investigating biological functions and tracking disease progression. ..

Article Title: SpaConTDS: A multimodal contrastive learning framework for identifying spatial domains by applying tuple disturbing strategy.
Article Snippet: .. In-depth exploration of the multimodal information within Spatial Transcriptomics (ST) data is essential for understanding the heterogeneity of tissue structure, investigating biological functions and tracking disease progression. ..

Sequencing:

Article Title: Single-cell and spatial transcriptomics unveils key regulators governing cell differentiation for Schistosoma sexual development
Article Snippet: .. The sequencing data from Stereo-seq spatial transcriptomics was processed using Stereo-seq Analysis Workflow (SAW) v8.0 ( https://en.stomics.tech ). ..

Article Title: SGMS2+ macrophages enhance NR4A3hi NK cell infiltration to improve prognosis and PD-1 treatment efficacy in hepatocellular carcinoma
Article Snippet: .. Spatial transcriptomics sequencing data were obtained from http://lifeome.net/supp/livercancer-st/data.htm and analyzed using Seurat in R. Subsequently, SCTtransform normalization was performed. ..



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Spatial Transcriptomics Inc breast cancer spatial transcriptomics st
Spatial organization and cell-cell communication networks in the tumor microenvironment. (A–C) The developmental trajectories of cell sub-populations from a spatial perspective are investigated. (D, E) Heatmap and network diagrams displaying cell–cell dependency analysis in the colocated, neighboring, and extended neighboring (15-point) regions of the spatial <t>transcriptomics</t> data. (F) The interaction heatmap visualized the intensity of intercellular interactions mediated by the ligand-receptor pairs. (G) The spatial cell communication network diagram illustrates that NUhighepi exhibit a higher intensity of cell communication with other cells. (H) Circos plot summarizing cell-type-specific interaction patterns.
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Spatial organization and cell-cell communication networks in the tumor microenvironment. (A–C) The developmental trajectories of cell sub-populations from a spatial perspective are investigated. (D, E) Heatmap and network diagrams displaying cell–cell dependency analysis in the colocated, neighboring, and extended neighboring (15-point) regions of the spatial transcriptomics data. (F) The interaction heatmap visualized the intensity of intercellular interactions mediated by the ligand-receptor pairs. (G) The spatial cell communication network diagram illustrates that NUhighepi exhibit a higher intensity of cell communication with other cells. (H) Circos plot summarizing cell-type-specific interaction patterns.

Journal: Frontiers in Oncology

Article Title: Spatial transcriptome and single-cell sequencing reveal the role of nucleotide metabolism in breast cancer progression and tumor microenvironment

doi: 10.3389/fonc.2025.1703778

Figure Lengend Snippet: Spatial organization and cell-cell communication networks in the tumor microenvironment. (A–C) The developmental trajectories of cell sub-populations from a spatial perspective are investigated. (D, E) Heatmap and network diagrams displaying cell–cell dependency analysis in the colocated, neighboring, and extended neighboring (15-point) regions of the spatial transcriptomics data. (F) The interaction heatmap visualized the intensity of intercellular interactions mediated by the ligand-receptor pairs. (G) The spatial cell communication network diagram illustrates that NUhighepi exhibit a higher intensity of cell communication with other cells. (H) Circos plot summarizing cell-type-specific interaction patterns.

Article Snippet: Breast cancer spatial transcriptomics (ST) data were acquired from the GEO database ( https://www.ncbi.nlm.nih.gov/geo/ ) and 10x Genomics official website ( https://www.10xgenomics.com/ ).

Techniques: