Review




Structured Review

Omics Data Automation spatial multi omics 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

Images

Related Articles

Biomarker Discovery:

Article Title: MultiSP deciphers tissue structure and multicellular communication from spatial multi-omics data
Article Snippet: .. • MultiSP deciphers complex tissue structures from spatial multi-omics data • Flexible integration of any number of omics modalities • MultiSP restores noisy and sparse spatial omics data • Inference of spatially multimodal cell-cell communication ..

Article Title: MultiSP deciphers tissue structure and multicellular communication from spatial multi-omics data.
Article Snippet: .. Highlights • MultiSP deciphers complex tissue structures from spatial multi-omics data • Flexible integration of any number of omics modalities • MultiSP restores noisy and sparse spatial omics data • Inference of spatially multimodal cell-cell communication Authors Chenfeng Mo, Xiufen Zou, Suoqin Jin Correspondence sqjin@whu.edu.cn In brief Mo et al. present MultiSP, an efficient deep learning framework for integrative analysis of spatial multi-omics data. ..

Article Title: Spatial integration of multi-omics data from serial sections using the novel Multi-Omics Imaging Integration Toolset
Article Snippet: .. Title: Spatial Integration of Multi-Omics Data from Serial Sections using the novel Multi-Omics Imaging Integration Toolset Version: Original Submission Date: 11/20/2024 ..

Article Title: Spatial integration of multi-omics data from serial sections using the novel Multi-Omics Imaging Integration Toolset
Article Snippet: .. Title: Spatial Integration of Multi-Omics Data from Serial Sections using the novel Multi-Omics Imaging Integration Toolset Version: Revision 1 Date: 2/24/2025 Reviewer name: Hua Zhang Reviewer Comments to Author: The quality of this manuscript has significantly improved in this revision. ..

Imaging:

Article Title: Spatial integration of multi-omics data from serial sections using the novel Multi-Omics Imaging Integration Toolset
Article Snippet: .. Title: Spatial Integration of Multi-Omics Data from Serial Sections using the novel Multi-Omics Imaging Integration Toolset Version: Original Submission Date: 11/20/2024 ..

Article Title: Spatial integration of multi-omics data from serial sections using the novel Multi-Omics Imaging Integration Toolset
Article Snippet: .. Title: Spatial Integration of Multi-Omics Data from Serial Sections using the novel Multi-Omics Imaging Integration Toolset Version: Revision 1 Date: 2/24/2025 Reviewer name: Hua Zhang Reviewer Comments to Author: The quality of this manuscript has significantly improved in this revision. ..

other:

Article Title: Construction of Gene Regulatory Networks Based on Spatial Multi-Omics Data and Application in Tumor-Boundary Analysis.
Article Snippet: Academic Editor: Xin Wang Received: 17 June 2025 Revised: 8 July 2025 Accepted: 9 July 2025 Published: 13 July 2025 Citation: Du, Y.; Xu, K.; Zhang, S.; Chen, L.; Liu, Z.; Xie, L. Construction of Gene Regulatory Networks Based on Spatial Multi-Omics Data and Application in Tumor-Boundary Analysis.

Article Title: SpaBalance: Balanced Learning for Efficient Spatial Multi-Omics Decoding.
Article Snippet: Deep Integration Model for Spatial Multi-Omics Data Analysis. a) SpaBalance model architecture.



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