… For our analysis, we used the cluster labels generated by Monocle as well as a set of labels
obtained via k-means clustering for a range of values of k, and, as in the original paper, we …

… The resulting data were visualized in SPRING and partitioned using Louvain clustering
on the SPRING k-nearest-neighbor graph. Four clusters were removed for quality control, …

… We apply k-means clustering (k = 10) to the top eight principal components of log-transformed
counts. Using this clustering, we identify the relevant clusters based on the reported …

… illustrate very well theminimum in the K¿ for the lanthanides around 7 M HCl, and the continuous
decrease in K¿ with increasing hydrochloric acid concentration for the actinide ions. …

… The coefficients m and n are determined by curve-fitting and the K's are the appropriate
stress-intensity factors. For self-similar crack extension in unidirectional composites, at least on a …

The tumor immune microenvironment plays a critical role in cancer progression and response
to immunotherapy in clear cell renal cell carcinoma (ccRCC), yet the composition and …

The continuous improvement of crop plants is essential for agriculture in the coming decades
and relies on the use of genetic variability through breeding. However, domestication and …

Single-cell transcriptomics can provide quantitative molecular signatures for large, unbiased
samples of the diverse cell types in the brain 1 , 2 – 3 . With the proliferation of multi-omics …

A detailed understanding of the paths that stem cells traverse to generate mature progeny is
vital for elucidating the mechanisms governing cell fate decisions and tissue homeostasis. …

… Specifically, for each of K clusters, we computed the average … Euclidean distance to obtain
a K × K distance matrix. This … voting from the k-nearest neighbor observed cells for k = 15. This …