The development and application of next-generation sequencing (NGS) technology and high-density SNP chips, as well as advanced statistical methods and bio-informatics tools have substantially improved the ability to detect genomic selected regions in livestock and poultry breeds. Selective signal detection...
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 ...
37,38. Histological examinations of the aged brain have shown that spine densities were reduced with aging in several cortical areas including the prefrontal cortex. In particular, the synapse density and
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...
Since the number of dimensions in our resultant matrix is high (780 features), we use a technique called HDBSCAN (hierarchical density-based spatial clustering of applications with noise) that identifies key clusters in the kinship space (given in Table 1). We set two parameters in the HDBSCAN...
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 increased density of endosomes, and to the use of fixative that has been shown to favor the clustering of synaptic vesicles [48,...
The original theory predicts that information density should be optimized on the time scale of individual processing fragments; here, what would matter is uniformity on a time-scale only fine-grained enough to avoid overloading comprehenders’ working memory. 5.3. The Bayesian Reader versus the ...
About 1.1 billion 100-bp paired-end reads generated on an Illumina HiSeq2000s machine were assembled using ALLPATHS-LG [125], from two paired-end (PE) and two mate pair (MP) libraries specifically designed for this algorithm (Additional file 1: Supplemental Note 1). Three libraries were ...
Unsupervised hierarchical clustering was conducted using the online software, Morpheus, (https://software.broadinstitute.org/morpheus/). Proximity between clusters was computed using complete linkages with Spearman rank correlations as the distance metric. The clustering algorithm works agglomeratively: initi...
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 layer. As an internal control data for cholera toxin labelling is also presented ...