tsne analysis software Search Results


cell imaging analysis live cell analysis software sartorius version tsne maaten  (Sartorius AG)
99
Sartorius AG cell imaging analysis live cell analysis software sartorius version tsne maaten
Cell Imaging Analysis Live Cell Analysis Software Sartorius Version Tsne Maaten, supplied by Sartorius AG, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/tsne+analysis+software/Live+Cell+Analysis+Instruments/pm40578364-711-65-67
Average 99 stars, based on 1 article reviews
cell imaging analysis live cell analysis software sartorius version tsne maaten - by Bioz Stars, 2026-10
99/100 stars
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tsne analysis  (RStudio)
90
RStudio tsne analysis
Tsne Analysis, supplied by RStudio, 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/tsne+analysis+software/rtsne+package/pmc05919077-232-9-14
Average 90 stars, based on 1 article reviews
tsne analysis - by Bioz Stars, 2026-10
90/100 stars
  Buy from Supplier
downsample plugin  (Becton Dickinson)
90
Becton Dickinson downsample plugin
FItSNE projection of the various cytokine-expressing cell subtypes in PBMC and RMC. Data from healthy donor PBMC (n=8) or RMC (n=11) samples, obtained via flow cytometry, were concatenated to generate a single FItSNE projection of the different unbiased cell clusters based on their cytokine and markers expression, calculated with FlowSOM. The FItSNE projection along with the percentage of events of each cell cluster for both PBMC (A, B) and RMC (C, D) are shown. FItSNE analysis was performed with the <t>tSNE</t> function <t>in</t> <t>FlowJo,</t> FItSNE algorithm, with 3000 iterations, and a perplexity of 20.0.
Downsample Plugin, 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
https://www.bioz.com/product/tsne+analysis+software/downsample+plugin/pmc10912472-88-2-4
Average 90 stars, based on 1 article reviews
downsample plugin - by Bioz Stars, 2026-10
90/100 stars
  Buy from Supplier
t stochastic neighbourhood embedding (tsne) algorithm  (Becton Dickinson)
90
Becton Dickinson t stochastic neighbourhood embedding (tsne) algorithm
FItSNE projection of the various cytokine-expressing cell subtypes in PBMC and RMC. Data from healthy donor PBMC (n=8) or RMC (n=11) samples, obtained via flow cytometry, were concatenated to generate a single FItSNE projection of the different unbiased cell clusters based on their cytokine and markers expression, calculated with FlowSOM. The FItSNE projection along with the percentage of events of each cell cluster for both PBMC (A, B) and RMC (C, D) are shown. FItSNE analysis was performed with the <t>tSNE</t> function <t>in</t> <t>FlowJo,</t> FItSNE algorithm, with 3000 iterations, and a perplexity of 20.0.
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
https://www.bioz.com/product/tsne+analysis+software/t+stochastic+neighbourhood+embedding++tsne++algorithm/pmc07577233-124-7-14
Average 90 stars, based on 1 article reviews
t stochastic neighbourhood embedding (tsne) algorithm - by Bioz Stars, 2026-10
90/100 stars
  Buy from Supplier

Image Search Results


FItSNE projection of the various cytokine-expressing cell subtypes in PBMC and RMC. Data from healthy donor PBMC (n=8) or RMC (n=11) samples, obtained via flow cytometry, were concatenated to generate a single FItSNE projection of the different unbiased cell clusters based on their cytokine and markers expression, calculated with FlowSOM. The FItSNE projection along with the percentage of events of each cell cluster for both PBMC (A, B) and RMC (C, D) are shown. FItSNE analysis was performed with the tSNE function in FlowJo, FItSNE algorithm, with 3000 iterations, and a perplexity of 20.0.

Journal: Frontiers in Immunology

Article Title: Comparative analysis of human gut- and blood-derived mononuclear cells: contrasts in function and phenotype

doi: 10.3389/fimmu.2024.1336480

Figure Lengend Snippet: FItSNE projection of the various cytokine-expressing cell subtypes in PBMC and RMC. Data from healthy donor PBMC (n=8) or RMC (n=11) samples, obtained via flow cytometry, were concatenated to generate a single FItSNE projection of the different unbiased cell clusters based on their cytokine and markers expression, calculated with FlowSOM. The FItSNE projection along with the percentage of events of each cell cluster for both PBMC (A, B) and RMC (C, D) are shown. FItSNE analysis was performed with the tSNE function in FlowJo, FItSNE algorithm, with 3000 iterations, and a perplexity of 20.0.

Article Snippet: For the tSNE analysis, FlowJo Downsample plugin was used to ensure similar number of events in all samples.

Techniques: Expressing, Flow Cytometry

FItSNE projection of the main cell groups among the various cytokine-expressing cell subtypes in PBMC and RMC. Layers of different cell populations were removed from the original tSNE projection for better visualization of the main cell groups in PBMC (n=8) and RMC (n=11); NK and other CD3- cells (A) , CD4 + and CD8 + T cells (B) , and γδ T cells are demonstrated (C) . FItSNE analysis was performed with the tSNE function in FlowJo, FItSNE algorithm, with 3000 iterations, and a perplexity of 20.0.

Journal: Frontiers in Immunology

Article Title: Comparative analysis of human gut- and blood-derived mononuclear cells: contrasts in function and phenotype

doi: 10.3389/fimmu.2024.1336480

Figure Lengend Snippet: FItSNE projection of the main cell groups among the various cytokine-expressing cell subtypes in PBMC and RMC. Layers of different cell populations were removed from the original tSNE projection for better visualization of the main cell groups in PBMC (n=8) and RMC (n=11); NK and other CD3- cells (A) , CD4 + and CD8 + T cells (B) , and γδ T cells are demonstrated (C) . FItSNE analysis was performed with the tSNE function in FlowJo, FItSNE algorithm, with 3000 iterations, and a perplexity of 20.0.

Article Snippet: For the tSNE analysis, FlowJo Downsample plugin was used to ensure similar number of events in all samples.

Techniques: Expressing