matrix decomposition Search Results


90
EcoDesign Inc matrix decomposition
Matrix Decomposition, supplied by EcoDesign Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Barents Group LLC cholesky decomposition matrix
Cholesky Decomposition Matrix, supplied by Barents Group LLC, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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cholesky decomposition matrix - by Bioz Stars, 2026-06
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Balzer GmbH matrix sign function decomposition with newton’s iterative method
Matrix Sign Function Decomposition With Newton’s Iterative Method, supplied by Balzer GmbH, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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matrix sign function decomposition with newton’s iterative method - by Bioz Stars, 2026-06
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Marhaba Laboratories eigenvector decomposition of the covariance or correlation matrix
Eigenvector Decomposition Of The Covariance Or Correlation Matrix, supplied by Marhaba Laboratories, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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IEEE Access spectral matrix decomposition-based motion artifacts removal in multi-channel ppg sensor signals
Spectral Matrix Decomposition Based Motion Artifacts Removal In Multi Channel Ppg Sensor Signals, supplied by IEEE Access, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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spectral matrix decomposition-based motion artifacts removal in multi-channel ppg sensor signals - by Bioz Stars, 2026-06
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86
Spatial Transcriptomics Inc matrix decomposition
Overview of EDGES. a) The inputs of EDGES consist of ST data and a reference scRNA‐seq data. EDGES partitions the ST and scRNA‐seq data into X 1 , X 2 , and X 3 according to the shared genes and constructs, a cell–cell proximity graph based on the spatial coordinates. b) The optimization problem of EDGES. EDGES employs a spatially constrained NMF <t>decomposition</t> strategy to obtain joint low‐dimensional representations for ST and scRNA‐seq data. c) The outputs of EDGES include a denoised ST gene expression profile for measured genes and the predicted expressions for undetected genes.
Matrix Decomposition, 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
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Average 86 stars, based on 1 article reviews
matrix decomposition - by Bioz Stars, 2026-06
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Overview of EDGES. a) The inputs of EDGES consist of ST data and a reference scRNA‐seq data. EDGES partitions the ST and scRNA‐seq data into X 1 , X 2 , and X 3 according to the shared genes and constructs, a cell–cell proximity graph based on the spatial coordinates. b) The optimization problem of EDGES. EDGES employs a spatially constrained NMF decomposition strategy to obtain joint low‐dimensional representations for ST and scRNA‐seq data. c) The outputs of EDGES include a denoised ST gene expression profile for measured genes and the predicted expressions for undetected genes.

Journal: Advanced Science

Article Title: Enhancing Spatial Transcriptomics via Spatially Constrained Matrix Decomposition with EDGES

doi: 10.1002/advs.202508346

Figure Lengend Snippet: Overview of EDGES. a) The inputs of EDGES consist of ST data and a reference scRNA‐seq data. EDGES partitions the ST and scRNA‐seq data into X 1 , X 2 , and X 3 according to the shared genes and constructs, a cell–cell proximity graph based on the spatial coordinates. b) The optimization problem of EDGES. EDGES employs a spatially constrained NMF decomposition strategy to obtain joint low‐dimensional representations for ST and scRNA‐seq data. c) The outputs of EDGES include a denoised ST gene expression profile for measured genes and the predicted expressions for undetected genes.

Article Snippet: Wu , and D. Sun , “ Enhancing Spatial Transcriptomics via Spatially Constrained Matrix Decomposition with EDGES .” Adv.

Techniques: Construct, Gene Expression