Rabies positive cells were assigned to one of the two components (i.e., superficial and deep layers) created by the clustering algorithm. Data is presented as the proportion of all rabies labelled cells in each
Automatic cell counting in MOp-ul was done as previously described20. A convolutional neural network was trained using H2B-GFP nuclear signalling. First, we develop an unsupervised detection algorithm for cell detection based on structure tensor and connected components analyses. Results were used to ...
With the popularity of unsupervised machine learning methods, the classical DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering algorithm (Ester et al., 1996) has recently drawn much attention. In practice, the DBSCAN algorithm has been successfully applied in cloud identific...
The clustering result for K = 4 indicated the presence of a clear division between the breeds with high egg-laying production (ZE, HY, and SC) and low egg-laying production (ST, ZD, and LH). This is also consistent with the results of the PCA and NJ tree. Fig. 1 Population ...
Early endosomes were significantly more numerous in DS fibroblasts as compared to 2 N fibroblasts (density increased by 75%). The clustering phenomenon observed by EM after chemical fixation in DS LCLs and fibroblasts was very rare after HPF, indicating that it could be an artefact due to ...
Fig. 21. Scatterplot of A2u parameters of monoporphyrin-lanthanoid coordination compounds (blue) and bis-porphyrinoids (green and orange), overlaid on a kernel density estimation plot. The increased density and clustering of similar compounds indicates that there are three distinct conformational cl...
Several of these constructions have good stability properties or good asymptotic behavior. However, as explained in [6], all of the known 1-parameter persistence strategies for handling outliers or variations in density share certain disadvantages: First, they all depend on a choice of a parameter...
This invited memoir looks back on my scientific career that straddles the solar and stellar branches of astrophysics, with sprinklings of historical contex
miRNAs and gene set scores were clustered using the hierarchical clustering algorithm, using Euclidean distance as distance metrics. The stability and statistical significance of the clusters were evaluated using the bootstrapping analysis (n = 10.000) implemented in th pvclust R package. ...
Using a diffusion map embedding algorithm, we identified gradient components, which estimated the low-dimensional embedding from the high-dimensional connectivity matrix. The algorithm is controlled by parameters α and t, where α controls the influence of the density of sampling points on the ...