multi omics spatial molecular data (Spatial Transcriptomics Inc)
86
Structured Review
Spatial Transcriptomics Inc
multi omics spatial molecular data
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, 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
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1) Product Images from "SEPAR enables spatial metagene discovery and associated molecular pattern characterization in spatial transcriptomics and multi-omics datasets"
Article Title: SEPAR enables spatial metagene discovery and associated molecular pattern characterization in spatial transcriptomics and multi-omics datasets
Journal: Communications Biology
doi: 10.1038/s42003-025-09340-w
Figure Legend 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.
Techniques Used: Gene Expression, Construct, Expressing, Biomarker Discovery
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