k-nn graph algorithm (MetaCell Inc)
90
Structured Review
MetaCell Inc
k-nn graph algorithm
K Nn Graph Algorithm, supplied by MetaCell 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/k-nn/k+nn+graph+algorithm/pmc11551150-267-5-1
Average 90 stars, based on 1 article reviews
K Nn Graph Algorithm, supplied by MetaCell 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/k-nn/k+nn+graph+algorithm/pmc11551150-267-5-1
Average 90 stars, based on 1 article reviews
k-nn graph algorithm - by Bioz Stars,
2026-11
90/100 stars
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Diffusion-based Assay:Article Title: Smad3 is essential for polarization of tumor-associated neutrophils in non-small cell lung carcinoma Article Snippet: A The arrows in the diffusion plot of RNA velocity analysis of the TAN dataset from Fig. indicates that the Smad3-KO N1 population (cluster 2, green) is derived from the Smad3-WT N2 (cluster 3, red) as shown by: B expression of neutrophil maturation markers, C expression of N1/N2 markers, and D the Article Title: BootCellNet, a resampling-based procedure, promotes unsupervised identification of cell populations via robust inference of gene regulatory networks Article Snippet: One can also use different smoothing methods, such as Article Title: BootCellNet, a resampling-based procedure, promotes unsupervised identification of cell populations via robust inference of gene regulatory networks. Article Snippet: One can also use different smoothing methods, such as Article Title: MetaCell: analysis of single-cell RNA-seq data using K -nn graph partitions Article Snippet: Smoothing based on Article Title: An immunosuppressive subtype of senescent tumor cells predicted worse immunotherapy response in lung adenocarcinoma Article Snippet: To address the bias introduced by this heterogeneity when selecting cells for subsequent weighted gene co-expression network analysis (WGCNA) analysis, we employed the non-parametric K-nn graph algorithm implemented in the Article Title: m 5 C related-regulator-mediated methylation modification patterns and prognostic significance in breast cancer Article Snippet: The Derivative Assay:Article Title: Smad3 is essential for polarization of tumor-associated neutrophils in non-small cell lung carcinoma Article Snippet: A The arrows in the diffusion plot of RNA velocity analysis of the TAN dataset from Fig. indicates that the Smad3-KO N1 population (cluster 2, green) is derived from the Smad3-WT N2 (cluster 3, red) as shown by: B expression of neutrophil maturation markers, C expression of N1/N2 markers, and D the Article Title: BootCellNet, a resampling-based procedure, promotes unsupervised identification of cell populations via robust inference of gene regulatory networks Article Snippet: One can also use different smoothing methods, such as Article Title: BootCellNet, a resampling-based procedure, promotes unsupervised identification of cell populations via robust inference of gene regulatory networks. Article Snippet: One can also use different smoothing methods, such as Article Title: MetaCell: analysis of single-cell RNA-seq data using K -nn graph partitions Article Snippet: Smoothing based on Article Title: An immunosuppressive subtype of senescent tumor cells predicted worse immunotherapy response in lung adenocarcinoma Article Snippet: To address the bias introduced by this heterogeneity when selecting cells for subsequent weighted gene co-expression network analysis (WGCNA) analysis, we employed the non-parametric K-nn graph algorithm implemented in the Article Title: m 5 C related-regulator-mediated methylation modification patterns and prognostic significance in breast cancer Article Snippet: The Expressing:Article Title: Smad3 is essential for polarization of tumor-associated neutrophils in non-small cell lung carcinoma Article Snippet: A The arrows in the diffusion plot of RNA velocity analysis of the TAN dataset from Fig. indicates that the Smad3-KO N1 population (cluster 2, green) is derived from the Smad3-WT N2 (cluster 3, red) as shown by: B expression of neutrophil maturation markers, C expression of N1/N2 markers, and D the Article Title: BootCellNet, a resampling-based procedure, promotes unsupervised identification of cell populations via robust inference of gene regulatory networks Article Snippet: One can also use different smoothing methods, such as Article Title: BootCellNet, a resampling-based procedure, promotes unsupervised identification of cell populations via robust inference of gene regulatory networks. Article Snippet: One can also use different smoothing methods, such as Article Title: MetaCell: analysis of single-cell RNA-seq data using K -nn graph partitions Article Snippet: Smoothing based on Article Title: An immunosuppressive subtype of senescent tumor cells predicted worse immunotherapy response in lung adenocarcinoma Article Snippet: To address the bias introduced by this heterogeneity when selecting cells for subsequent weighted gene co-expression network analysis (WGCNA) analysis, we employed the non-parametric K-nn graph algorithm implemented in the Article Title: m 5 C related-regulator-mediated methylation modification patterns and prognostic significance in breast cancer Article Snippet: The Gene Expression:Article Title: Smad3 is essential for polarization of tumor-associated neutrophils in non-small cell lung carcinoma Article Snippet: A The arrows in the diffusion plot of RNA velocity analysis of the TAN dataset from Fig. indicates that the Smad3-KO N1 population (cluster 2, green) is derived from the Smad3-WT N2 (cluster 3, red) as shown by: B expression of neutrophil maturation markers, C expression of N1/N2 markers, and D the Article Title: BootCellNet, a resampling-based procedure, promotes unsupervised identification of cell populations via robust inference of gene regulatory networks Article Snippet: One can also use different smoothing methods, such as Article Title: BootCellNet, a resampling-based procedure, promotes unsupervised identification of cell populations via robust inference of gene regulatory networks. Article Snippet: One can also use different smoothing methods, such as Article Title: MetaCell: analysis of single-cell RNA-seq data using K -nn graph partitions Article Snippet: Smoothing based on Article Title: An immunosuppressive subtype of senescent tumor cells predicted worse immunotherapy response in lung adenocarcinoma Article Snippet: To address the bias introduced by this heterogeneity when selecting cells for subsequent weighted gene co-expression network analysis (WGCNA) analysis, we employed the non-parametric K-nn graph algorithm implemented in the Article Title: m 5 C related-regulator-mediated methylation modification patterns and prognostic significance in breast cancer Article Snippet: The |