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

 
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    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/multi+omics+spatial+molecular+data/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, 2026-10
    86/100 stars

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    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.

    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. ..

    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 ]. ..



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    multi omics spatial molecular data  (Spatial Transcriptomics Inc)
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    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/multi+omics+spatial+molecular+data/cell+single/pmc12820152-293-39-6
    Average 86 stars, based on 1 article reviews
    multi omics spatial molecular data - by Bioz Stars, 2026-10
    86/100 stars
    		  Buy from Supplier

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    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