Review



plant single cell spatial multi omics research spatial transcriptomics st  (Spatial Transcriptomics Inc)

 
  • Logo
  • About
  • News
  • Press Release
  • Team
  • Advisors
  • Partners
  • Contact
  • Bioz Stars
  • Bioz vStars
  • 86

    Structured Review

    Spatial Transcriptomics Inc plant single cell spatial multi omics research spatial transcriptomics st
    Plant Single Cell Spatial Multi Omics Research Spatial Transcriptomics St, 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+multi-omics/spatial+st+technologies+transcriptomics/pm41162237-17-2-7
    Average 86 stars, based on 1 article reviews
    plant single cell spatial multi omics research spatial transcriptomics st - by Bioz Stars, 2026-09
    86/100 stars

    Images

    Related Articles

    Spatial Transcriptomics:

    Article Title: A technical comparison of spatial transcriptomics platforms across six cancer types.
    Article Snippet: .. Background Spatial transcriptomics (ST) technologies are reshaping our understanding of tissue organization and cellular context in health and disease. ..

    Article Title: Mapping biology in space: from spatial transcriptomics platforms to analytical tools and databases.
    Article Snippet: .. Spatial transcriptomics (ST) technologies have addressed this gap by enabling the quantification of gene expression in intact tissue sections, preserving both spatial localization and, in some cases, the three-dimensional (3D) architecture of molecular processes. ..

    Article Title: SpaLLM: a general framework for spatial domain identification with large language models
    Article Snippet: .. Spatial transcriptomics (ST) technologies have revolutionized our understanding of tissue architecture by enabling simultaneous measurement of gene expression and spatial location information ( ; ; ). ..

    Article Title: SpaLLM: a general framework for spatial domain identification with large language models
    Article Snippet: .. Spatial transcriptomics (ST) technologies enable the profiling of gene expression while preserving spatial context, offering unprecedented insights into tissue organization. ..

    Article Title: Reconstructing Coherent Functional Landscape From Multi-Modal Multi-Slice Spatial Transcriptomics by a Variational Spatial Gaussian Process.
    Article Snippet: .. Spatial transcriptomics (ST) technologies enable highthroughput gene expression profiling while preserving spatial context within tissues in situ [ 1–5 ]. ..

    Article Title: A technical comparison of spatial transcriptomics platforms across six cancer types.
    Article Snippet: .. Spatial transcriptomics (ST) technologies are reshaping our understanding of tissue organization and cellular context in health and disease. ..

    other:

    Article Title: Comprehensive benchmarking of batch integration methods for spatial transcriptomics using a large-scale cancer atlas
    Article Snippet: Spatial transcriptomics (ST) technologies capture mRNA counts with spatial context, complementing singlecell and bulk transcriptomics.

    Gene Expression:

    Article Title: Mapping biology in space: from spatial transcriptomics platforms to analytical tools and databases.
    Article Snippet: .. Spatial transcriptomics (ST) technologies have addressed this gap by enabling the quantification of gene expression in intact tissue sections, preserving both spatial localization and, in some cases, the three-dimensional (3D) architecture of molecular processes. ..

    Article Title: SpaLLM: a general framework for spatial domain identification with large language models
    Article Snippet: .. Spatial transcriptomics (ST) technologies have revolutionized our understanding of tissue architecture by enabling simultaneous measurement of gene expression and spatial location information ( ; ; ). ..

    Article Title: Robust and interpretable prediction of gene markers and cell types from spatial transcriptomics data.
    Article Snippet: .. 24 Spatial transcriptomics (ST) links tissue morphology with gene expression values, opening new avenues for digital pathology. ..

    Article Title: SpaLLM: a general framework for spatial domain identification with large language models
    Article Snippet: .. Spatial transcriptomics (ST) technologies enable the profiling of gene expression while preserving spatial context, offering unprecedented insights into tissue organization. ..

    Article Title: Reconstructing Coherent Functional Landscape From Multi-Modal Multi-Slice Spatial Transcriptomics by a Variational Spatial Gaussian Process.
    Article Snippet: .. Spatial transcriptomics (ST) technologies enable highthroughput gene expression profiling while preserving spatial context within tissues in situ [ 1–5 ]. ..

    Preserving:

    Article Title: Mapping biology in space: from spatial transcriptomics platforms to analytical tools and databases.
    Article Snippet: .. Spatial transcriptomics (ST) technologies have addressed this gap by enabling the quantification of gene expression in intact tissue sections, preserving both spatial localization and, in some cases, the three-dimensional (3D) architecture of molecular processes. ..

    Article Title: SpaLLM: a general framework for spatial domain identification with large language models
    Article Snippet: .. Spatial transcriptomics (ST) technologies enable the profiling of gene expression while preserving spatial context, offering unprecedented insights into tissue organization. ..

    Article Title: Reconstructing Coherent Functional Landscape From Multi-Modal Multi-Slice Spatial Transcriptomics by a Variational Spatial Gaussian Process.
    Article Snippet: .. Spatial transcriptomics (ST) technologies enable highthroughput gene expression profiling while preserving spatial context within tissues in situ [ 1–5 ]. ..

    High Throughput Screening Assay:

    Article Title: Reconstructing Coherent Functional Landscape From Multi-Modal Multi-Slice Spatial Transcriptomics by a Variational Spatial Gaussian Process.
    Article Snippet: .. Spatial transcriptomics (ST) technologies enable highthroughput gene expression profiling while preserving spatial context within tissues in situ [ 1–5 ]. ..

    In Situ:

    Article Title: Reconstructing Coherent Functional Landscape From Multi-Modal Multi-Slice Spatial Transcriptomics by a Variational Spatial Gaussian Process.
    Article Snippet: .. Spatial transcriptomics (ST) technologies enable highthroughput gene expression profiling while preserving spatial context within tissues in situ [ 1–5 ]. ..



    Similar Products

    86
    Spatial Transcriptomics Inc multi omics spatial molecular data
    a SEPAR is a framework based on graph-regularized NMF designed to identify spatially aware metagene patterns using both spatial location and gene expression as input. Spatial location data is leveraged to construct weighted graph regularization capturing the spatial relationships of the spots or cells. Sparsity regularization and dissimilarity regularization are applied to ensure distinct spatial metagene patterns. b SEPAR supports efficient and robust downstream analyses of SRT data, including metagene expression pattern recognition, pattern-specific gene analysis, SVG identification, spatial domain delineation, gene expression denoising and <t>spatial</t> <t>multi-omics</t> data analysis.
    Multi Omics Spatial Molecular 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/spatial+multi-omics/cell+single/pmc12820152-293-39-6
    Average 86 stars, based on 1 article reviews
    multi omics spatial molecular data - by Bioz Stars, 2026-09
    86/100 stars
      Buy from Supplier

    86
    Spatial Transcriptomics Inc spatial multi omics technologies
    a SEPAR is a framework based on graph-regularized NMF designed to identify spatially aware metagene patterns using both spatial location and gene expression as input. Spatial location data is leveraged to construct weighted graph regularization capturing the spatial relationships of the spots or cells. Sparsity regularization and dissimilarity regularization are applied to ensure distinct spatial metagene patterns. b SEPAR supports efficient and robust downstream analyses of SRT data, including metagene expression pattern recognition, pattern-specific gene analysis, SVG identification, spatial domain delineation, gene expression denoising and <t>spatial</t> <t>multi-omics</t> data analysis.
    Spatial Multi Omics Technologies, 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+multi-omics/cell+single/pmc12626878-191-4-8
    Average 86 stars, based on 1 article reviews
    spatial multi omics technologies - by Bioz Stars, 2026-09
    86/100 stars
      Buy from Supplier

    86
    Spatial Transcriptomics Inc spatial multi omics validate glycolysis preference
    a SEPAR is a framework based on graph-regularized NMF designed to identify spatially aware metagene patterns using both spatial location and gene expression as input. Spatial location data is leveraged to construct weighted graph regularization capturing the spatial relationships of the spots or cells. Sparsity regularization and dissimilarity regularization are applied to ensure distinct spatial metagene patterns. b SEPAR supports efficient and robust downstream analyses of SRT data, including metagene expression pattern recognition, pattern-specific gene analysis, SVG identification, spatial domain delineation, gene expression denoising and <t>spatial</t> <t>multi-omics</t> data analysis.
    Spatial Multi Omics Validate Glycolysis Preference, 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+multi-omics/cell+single/pm41253274-9-220-231
    Average 86 stars, based on 1 article reviews
    spatial multi omics validate glycolysis preference - by Bioz Stars, 2026-09
    86/100 stars
      Buy from Supplier

    86
    Spatial Transcriptomics Inc plant single cell spatial multi omics research spatial transcriptomics st
    a SEPAR is a framework based on graph-regularized NMF designed to identify spatially aware metagene patterns using both spatial location and gene expression as input. Spatial location data is leveraged to construct weighted graph regularization capturing the spatial relationships of the spots or cells. Sparsity regularization and dissimilarity regularization are applied to ensure distinct spatial metagene patterns. b SEPAR supports efficient and robust downstream analyses of SRT data, including metagene expression pattern recognition, pattern-specific gene analysis, SVG identification, spatial domain delineation, gene expression denoising and <t>spatial</t> <t>multi-omics</t> data analysis.
    Plant Single Cell Spatial Multi Omics Research Spatial Transcriptomics St, 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+multi-omics/spatial+st+technologies+transcriptomics/pm41162237-17-2-7
    Average 86 stars, based on 1 article reviews
    plant single cell spatial multi omics research spatial transcriptomics st - by Bioz Stars, 2026-09
    86/100 stars
      Buy from Supplier

    86
    Omics Data Automation spatial multi omics data analysis
    a SEPAR is a framework based on graph-regularized NMF designed to identify spatially aware metagene patterns using both spatial location and gene expression as input. Spatial location data is leveraged to construct weighted graph regularization capturing the spatial relationships of the spots or cells. Sparsity regularization and dissimilarity regularization are applied to ensure distinct spatial metagene patterns. b SEPAR supports efficient and robust downstream analyses of SRT data, including metagene expression pattern recognition, pattern-specific gene analysis, SVG identification, spatial domain delineation, gene expression denoising and <t>spatial</t> <t>multi-omics</t> data analysis.
    Spatial Multi Omics Data Analysis, supplied by Omics Data Automation, 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+multi-omics/analysis+data+multi+omics/pm41085010-113-4-5
    Average 86 stars, based on 1 article reviews
    spatial multi omics data analysis - by Bioz Stars, 2026-09
    86/100 stars
      Buy from Supplier

    86
    Omics Data Automation spatial multi omics data
    a SEPAR is a framework based on graph-regularized NMF designed to identify spatially aware metagene patterns using both spatial location and gene expression as input. Spatial location data is leveraged to construct weighted graph regularization capturing the spatial relationships of the spots or cells. Sparsity regularization and dissimilarity regularization are applied to ensure distinct spatial metagene patterns. b SEPAR supports efficient and robust downstream analyses of SRT data, including metagene expression pattern recognition, pattern-specific gene analysis, SVG identification, spatial domain delineation, gene expression denoising and <t>spatial</t> <t>multi-omics</t> data analysis.
    Spatial Multi Omics Data, supplied by Omics Data Automation, 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+multi-omics/analysis+data+multi+omics/pm40725477-10-40-41
    Average 86 stars, based on 1 article reviews
    spatial multi omics data - by Bioz Stars, 2026-09
    86/100 stars
      Buy from Supplier

    86
    Spatial Transcriptomics Inc high sensitivity spatial multi omics technologies
    a SEPAR is a framework based on graph-regularized NMF designed to identify spatially aware metagene patterns using both spatial location and gene expression as input. Spatial location data is leveraged to construct weighted graph regularization capturing the spatial relationships of the spots or cells. Sparsity regularization and dissimilarity regularization are applied to ensure distinct spatial metagene patterns. b SEPAR supports efficient and robust downstream analyses of SRT data, including metagene expression pattern recognition, pattern-specific gene analysis, SVG identification, spatial domain delineation, gene expression denoising and <t>spatial</t> <t>multi-omics</t> data analysis.
    High Sensitivity Spatial Multi Omics Technologies, 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+multi-omics/cell+single/10__54254_slash_2755___2721_slash_2025__po25414-135-4-11
    Average 86 stars, based on 1 article reviews
    high sensitivity spatial multi omics technologies - by Bioz Stars, 2026-09
    86/100 stars
      Buy from Supplier

    90
    Spatial Transcriptomics Inc spatial integration of multi-omics
    a SEPAR is a framework based on graph-regularized NMF designed to identify spatially aware metagene patterns using both spatial location and gene expression as input. Spatial location data is leveraged to construct weighted graph regularization capturing the spatial relationships of the spots or cells. Sparsity regularization and dissimilarity regularization are applied to ensure distinct spatial metagene patterns. b SEPAR supports efficient and robust downstream analyses of SRT data, including metagene expression pattern recognition, pattern-specific gene analysis, SVG identification, spatial domain delineation, gene expression denoising and <t>spatial</t> <t>multi-omics</t> data analysis.
    Spatial Integration Of Multi Omics, 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+multi-omics/spatial+omics/pm40563563-255-137-152
    Average 90 stars, based on 1 article reviews
    spatial integration of multi-omics - by Bioz Stars, 2026-09
    90/100 stars
      Buy from Supplier

    90
    Epigenomics ag spatial multi-omics
    a SEPAR is a framework based on graph-regularized NMF designed to identify spatially aware metagene patterns using both spatial location and gene expression as input. Spatial location data is leveraged to construct weighted graph regularization capturing the spatial relationships of the spots or cells. Sparsity regularization and dissimilarity regularization are applied to ensure distinct spatial metagene patterns. b SEPAR supports efficient and robust downstream analyses of SRT data, including metagene expression pattern recognition, pattern-specific gene analysis, SVG identification, spatial domain delineation, gene expression denoising and <t>spatial</t> <t>multi-omics</t> data analysis.
    Spatial Multi Omics, supplied by Epigenomics ag, 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+multi-omics/multi+epigenomics+approach/pm40461389-41-0-12
    Average 90 stars, based on 1 article reviews
    spatial multi-omics - by Bioz Stars, 2026-09
    90/100 stars
      Buy from Supplier

    90
    Spatial Transcriptomics Inc spatial multi-omics geomx
    Technologies for assaying intratumoral heterogeneity.
    Spatial Multi Omics Geomx, 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+multi-omics/spatial+omics/pmc11816170-14-0-8
    Average 90 stars, based on 1 article reviews
    spatial multi-omics geomx - by Bioz Stars, 2026-09
    90/100 stars
      Buy from Supplier

    Image Search Results


    a SEPAR is a framework based on graph-regularized NMF designed to identify spatially aware metagene patterns using both spatial location and gene expression as input. Spatial location data is leveraged to construct weighted graph regularization capturing the spatial relationships of the spots or cells. Sparsity regularization and dissimilarity regularization are applied to ensure distinct spatial metagene patterns. b SEPAR supports efficient and robust downstream analyses of SRT data, including metagene expression pattern recognition, pattern-specific gene analysis, SVG identification, spatial domain delineation, gene expression denoising and spatial multi-omics data analysis.

    Journal: Communications Biology

    Article Title: SEPAR enables spatial metagene discovery and associated molecular pattern characterization in spatial transcriptomics and multi-omics datasets

    doi: 10.1038/s42003-025-09340-w

    Figure Lengend Snippet: a SEPAR is a framework based on graph-regularized NMF designed to identify spatially aware metagene patterns using both spatial location and gene expression as input. Spatial location data is leveraged to construct weighted graph regularization capturing the spatial relationships of the spots or cells. Sparsity regularization and dissimilarity regularization are applied to ensure distinct spatial metagene patterns. b SEPAR supports efficient and robust downstream analyses of SRT data, including metagene expression pattern recognition, pattern-specific gene analysis, SVG identification, spatial domain delineation, gene expression denoising and spatial multi-omics data analysis.

    Article Snippet: Beyond demonstrating robust performance in diverse spatial transcriptomics technologies (10 × Visium, Stereo-seq, osmFISH and MERFISH), where SEPAR consistently identified biologically meaningful spatial patterns and revealed tissue-specific expression programs across different resolution scales and measurement principles, SEPAR effectively handles multi-omics spatial molecular data.

    Techniques: Gene Expression, Construct, Expressing, Biomarker Discovery

    Technologies for assaying intratumoral heterogeneity.

    Journal: Cancers

    Article Title: Heterogeneity in Cancer

    doi: 10.3390/cancers17030441

    Figure Lengend Snippet: Technologies for assaying intratumoral heterogeneity.

    Article Snippet: Spatial multi-omics (e.g., GeoMX) , Combines IF with spatial transcriptomics through UV cleavage of ROIs , High-throughput spatial profiling of both transcriptome and protein panel in a tissue sample , [ ] .

    Techniques: Gene Expression, Fluorescence, Expressing, Protein-Protein interactions, Activity Assay, In Situ, Biomarker Discovery