t-sne implementation Search Results


stochastic neighbor embedding t sne toolbox  (MathWorks Inc)
96
MathWorks Inc stochastic neighbor embedding t sne toolbox
Data is processed through a traditional pipeline of RNA-seq data preprocessing and differential expression genes (DEGs) extraction using specific filter parameters such as False Discovery Rate (FDR) <0.05 and fold change (FC) >1.5. The data are utilized to construct a correlation matrix, its correlation heatmap is generated to visualize DEGs’ correlation distribution. For further analysis, the absolute values of the correlations are ordered. The sorted heatmap aids in the visualization of the top genes. Clustering is performed using Dendrogram, Principal Component Analysis (PCA), and t-distributed <t>Stochastic</t> <t>Neighbor</t> <t>Embedding</t> (t-SNE) methods, followed by distance thresholding (for the Dendrogram results) or K-means (for the PCA and t-SNE results) for finer clustering. Clusters were analyzed via STRING or network analysis to identify potential target genes. All pathways, including generated and existing ones from databases like GO and KEGG, are quantitatively compared using novel indices and ranked for relevance.
Stochastic Neighbor Embedding T Sne Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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t-sne  (MathWorks Inc)
90
MathWorks Inc t-sne
Data is processed through a traditional pipeline of RNA-seq data preprocessing and differential expression genes (DEGs) extraction using specific filter parameters such as False Discovery Rate (FDR) <0.05 and fold change (FC) >1.5. The data are utilized to construct a correlation matrix, its correlation heatmap is generated to visualize DEGs’ correlation distribution. For further analysis, the absolute values of the correlations are ordered. The sorted heatmap aids in the visualization of the top genes. Clustering is performed using Dendrogram, Principal Component Analysis (PCA), and t-distributed <t>Stochastic</t> <t>Neighbor</t> <t>Embedding</t> (t-SNE) methods, followed by distance thresholding (for the Dendrogram results) or K-means (for the PCA and t-SNE results) for finer clustering. Clusters were analyzed via STRING or network analysis to identify potential target genes. All pathways, including generated and existing ones from databases like GO and KEGG, are quantitatively compared using novel indices and ranked for relevance.
T Sne, supplied by MathWorks 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/result/t-sne/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
t-sne - by Bioz Stars, 2026-04
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matlab 2016b  (MathWorks Inc)
90
MathWorks Inc matlab 2016b
Data is processed through a traditional pipeline of RNA-seq data preprocessing and differential expression genes (DEGs) extraction using specific filter parameters such as False Discovery Rate (FDR) <0.05 and fold change (FC) >1.5. The data are utilized to construct a correlation matrix, its correlation heatmap is generated to visualize DEGs’ correlation distribution. For further analysis, the absolute values of the correlations are ordered. The sorted heatmap aids in the visualization of the top genes. Clustering is performed using Dendrogram, Principal Component Analysis (PCA), and t-distributed <t>Stochastic</t> <t>Neighbor</t> <t>Embedding</t> (t-SNE) methods, followed by distance thresholding (for the Dendrogram results) or K-means (for the PCA and t-SNE results) for finer clustering. Clusters were analyzed via STRING or network analysis to identify potential target genes. All pathways, including generated and existing ones from databases like GO and KEGG, are quantitatively compared using novel indices and ranked for relevance.
Matlab 2016b, supplied by MathWorks 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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Average 90 stars, based on 1 article reviews
matlab 2016b - by Bioz Stars, 2026-04
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t-sne implementation  (MathWorks Inc)
90
MathWorks Inc t-sne implementation
a – d , Clustering through t <t>-SNE</t> of reaction presence across all pathways per reconstruction. Coordinates were statistically different across taxonomic units (Kruskal–Wallis test, P = 0.0001 in all cases). a , Members of the largest classes. b , Members of the largest families. c , Members of the Bacilli class by genus. d , Members of the Gammaproteobacteria class by genus. e – h , Features of all AGORA2 reconstructions across phyla: e , Number of reactions. f , Number of metabolites. g , Number of genes. h , growth rate in h −1 on aerobic Western diet.
T Sne Implementation, supplied by MathWorks 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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Average 90 stars, based on 1 article reviews
t-sne implementation - by Bioz Stars, 2026-04
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t-sne toolbox  (MathWorks Inc)
90
MathWorks Inc t-sne toolbox
a – d , Clustering through t <t>-SNE</t> of reaction presence across all pathways per reconstruction. Coordinates were statistically different across taxonomic units (Kruskal–Wallis test, P = 0.0001 in all cases). a , Members of the largest classes. b , Members of the largest families. c , Members of the Bacilli class by genus. d , Members of the Gammaproteobacteria class by genus. e – h , Features of all AGORA2 reconstructions across phyla: e , Number of reactions. f , Number of metabolites. g , Number of genes. h , growth rate in h −1 on aerobic Western diet.
T Sne Toolbox, supplied by MathWorks 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/result/t-sne toolbox/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
t-sne toolbox - by Bioz Stars, 2026-04
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t-stochastic neighborhood embedding (t-sne) algorithm  (Becton Dickinson)
90
Becton Dickinson t-stochastic neighborhood embedding (t-sne) algorithm
a – d , Clustering through t <t>-SNE</t> of reaction presence across all pathways per reconstruction. Coordinates were statistically different across taxonomic units (Kruskal–Wallis test, P = 0.0001 in all cases). a , Members of the largest classes. b , Members of the largest families. c , Members of the Bacilli class by genus. d , Members of the Gammaproteobacteria class by genus. e – h , Features of all AGORA2 reconstructions across phyla: e , Number of reactions. f , Number of metabolites. g , Number of genes. h , growth rate in h −1 on aerobic Western diet.
T Stochastic Neighborhood Embedding (T Sne) Algorithm, supplied by Becton Dickinson, 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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Average 90 stars, based on 1 article reviews
t-stochastic neighborhood embedding (t-sne) algorithm - by Bioz Stars, 2026-04
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t-sne matlab implementation  (MathWorks Inc)
90
MathWorks Inc t-sne matlab implementation
a – d , Clustering through t <t>-SNE</t> of reaction presence across all pathways per reconstruction. Coordinates were statistically different across taxonomic units (Kruskal–Wallis test, P = 0.0001 in all cases). a , Members of the largest classes. b , Members of the largest families. c , Members of the Bacilli class by genus. d , Members of the Gammaproteobacteria class by genus. e – h , Features of all AGORA2 reconstructions across phyla: e , Number of reactions. f , Number of metabolites. g , Number of genes. h , growth rate in h −1 on aerobic Western diet.
T Sne Matlab Implementation, supplied by MathWorks 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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Average 90 stars, based on 1 article reviews
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t-distributed stochastic neighbor embedding implementation for  (MathWorks Inc)
90
MathWorks Inc t-distributed stochastic neighbor embedding implementation for
a – d , Clustering through t <t>-SNE</t> of reaction presence across all pathways per reconstruction. Coordinates were statistically different across taxonomic units (Kruskal–Wallis test, P = 0.0001 in all cases). a , Members of the largest classes. b , Members of the largest families. c , Members of the Bacilli class by genus. d , Members of the Gammaproteobacteria class by genus. e – h , Features of all AGORA2 reconstructions across phyla: e , Number of reactions. f , Number of metabolites. g , Number of genes. h , growth rate in h −1 on aerobic Western diet.
T Distributed Stochastic Neighbor Embedding Implementation For, supplied by MathWorks 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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t-distributed stochastic neighbor embedding implementation for - by Bioz Stars, 2026-04
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matlab implementation tsne  (MathWorks Inc)
90
MathWorks Inc matlab implementation tsne
a – d , Clustering through t <t>-SNE</t> of reaction presence across all pathways per reconstruction. Coordinates were statistically different across taxonomic units (Kruskal–Wallis test, P = 0.0001 in all cases). a , Members of the largest classes. b , Members of the largest families. c , Members of the Bacilli class by genus. d , Members of the Gammaproteobacteria class by genus. e – h , Features of all AGORA2 reconstructions across phyla: e , Number of reactions. f , Number of metabolites. g , Number of genes. h , growth rate in h −1 on aerobic Western diet.
Matlab Implementation Tsne, supplied by MathWorks 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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matlab implementation tsne - by Bioz Stars, 2026-04
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tsne function  (MathWorks Inc)
90
MathWorks Inc tsne function
a – d , Clustering through t <t>-SNE</t> of reaction presence across all pathways per reconstruction. Coordinates were statistically different across taxonomic units (Kruskal–Wallis test, P = 0.0001 in all cases). a , Members of the largest classes. b , Members of the largest families. c , Members of the Bacilli class by genus. d , Members of the Gammaproteobacteria class by genus. e – h , Features of all AGORA2 reconstructions across phyla: e , Number of reactions. f , Number of metabolites. g , Number of genes. h , growth rate in h −1 on aerobic Western diet.
Tsne Function, supplied by MathWorks 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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t stochastic neighbourhood embedding (tsne) algorithm  (Becton Dickinson)
90
Becton Dickinson t stochastic neighbourhood embedding (tsne) algorithm
a – d , Clustering through t <t>-SNE</t> of reaction presence across all pathways per reconstruction. Coordinates were statistically different across taxonomic units (Kruskal–Wallis test, P = 0.0001 in all cases). a , Members of the largest classes. b , Members of the largest families. c , Members of the Bacilli class by genus. d , Members of the Gammaproteobacteria class by genus. e – h , Features of all AGORA2 reconstructions across phyla: e , Number of reactions. f , Number of metabolites. g , Number of genes. h , growth rate in h −1 on aerobic Western diet.
T Stochastic Neighbourhood Embedding (Tsne) Algorithm, supplied by Becton Dickinson, 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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t-sne implementation in  (MathWorks Inc)
90
MathWorks Inc t-sne implementation in
a – d , Clustering through t <t>-SNE</t> of reaction presence across all pathways per reconstruction. Coordinates were statistically different across taxonomic units (Kruskal–Wallis test, P = 0.0001 in all cases). a , Members of the largest classes. b , Members of the largest families. c , Members of the Bacilli class by genus. d , Members of the Gammaproteobacteria class by genus. e – h , Features of all AGORA2 reconstructions across phyla: e , Number of reactions. f , Number of metabolites. g , Number of genes. h , growth rate in h −1 on aerobic Western diet.
T Sne Implementation In, supplied by MathWorks 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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Image Search Results


Data is processed through a traditional pipeline of RNA-seq data preprocessing and differential expression genes (DEGs) extraction using specific filter parameters such as False Discovery Rate (FDR) <0.05 and fold change (FC) >1.5. The data are utilized to construct a correlation matrix, its correlation heatmap is generated to visualize DEGs’ correlation distribution. For further analysis, the absolute values of the correlations are ordered. The sorted heatmap aids in the visualization of the top genes. Clustering is performed using Dendrogram, Principal Component Analysis (PCA), and t-distributed Stochastic Neighbor Embedding (t-SNE) methods, followed by distance thresholding (for the Dendrogram results) or K-means (for the PCA and t-SNE results) for finer clustering. Clusters were analyzed via STRING or network analysis to identify potential target genes. All pathways, including generated and existing ones from databases like GO and KEGG, are quantitatively compared using novel indices and ranked for relevance.

Journal: bioRxiv

Article Title: Identification Drug Targets for Oxaliplatin-Induced Cardiotoxicity without Affecting Cancer Treatment through Inter Variability Cross-Correlation Analysis (IVCCA)

doi: 10.1101/2024.02.11.579390

Figure Lengend Snippet: Data is processed through a traditional pipeline of RNA-seq data preprocessing and differential expression genes (DEGs) extraction using specific filter parameters such as False Discovery Rate (FDR) <0.05 and fold change (FC) >1.5. The data are utilized to construct a correlation matrix, its correlation heatmap is generated to visualize DEGs’ correlation distribution. For further analysis, the absolute values of the correlations are ordered. The sorted heatmap aids in the visualization of the top genes. Clustering is performed using Dendrogram, Principal Component Analysis (PCA), and t-distributed Stochastic Neighbor Embedding (t-SNE) methods, followed by distance thresholding (for the Dendrogram results) or K-means (for the PCA and t-SNE results) for finer clustering. Clusters were analyzed via STRING or network analysis to identify potential target genes. All pathways, including generated and existing ones from databases like GO and KEGG, are quantitatively compared using novel indices and ranked for relevance.

Article Snippet: Our implemented t-distributed Stochastic Neighbor Embedding (t-SNE) toolbox that performs t-SNE calculations ( ) uses the results from the correlation matrix and presents the genes based on their correlation values in 3D using a built-in ‘ tsne ’ function implemented in MATLAB.

Techniques: RNA Sequencing Assay, Expressing, Extraction, Construct, Generated

a – d , Clustering through t -SNE of reaction presence across all pathways per reconstruction. Coordinates were statistically different across taxonomic units (Kruskal–Wallis test, P = 0.0001 in all cases). a , Members of the largest classes. b , Members of the largest families. c , Members of the Bacilli class by genus. d , Members of the Gammaproteobacteria class by genus. e – h , Features of all AGORA2 reconstructions across phyla: e , Number of reactions. f , Number of metabolites. g , Number of genes. h , growth rate in h −1 on aerobic Western diet.

Journal: Nature Biotechnology

Article Title: Genome-scale metabolic reconstruction of 7,302 human microorganisms for personalized medicine

doi: 10.1038/s41587-022-01628-0

Figure Lengend Snippet: a – d , Clustering through t -SNE of reaction presence across all pathways per reconstruction. Coordinates were statistically different across taxonomic units (Kruskal–Wallis test, P = 0.0001 in all cases). a , Members of the largest classes. b , Members of the largest families. c , Members of the Bacilli class by genus. d , Members of the Gammaproteobacteria class by genus. e – h , Features of all AGORA2 reconstructions across phyla: e , Number of reactions. f , Number of metabolites. g , Number of genes. h , growth rate in h −1 on aerobic Western diet.

Article Snippet: Clustering of taxa by reaction presence through t -distributed stochastic neighbor embedding ( t -SNE) was performed using the t -SNE implementation in MATLAB with Euclidean distance, barneshut set as the algorithm and perplexity set to 30.

Techniques: Western Blot