https://www.selleckchem.com/products/mk-8719.html
Principal component analysis (PCA) and two of the widely used cluster analysis tools, namely, K-means and Density-based Spatial Clustering of Applications with Noise (DBSCAN), were explored for clustering and feature representation of varied analytical datasets. It has been shown that the clustering patterns delineated by the used algorithms changed based on the included chromatographic profiles. The applied data analysis tools were found effective in revealing patterns of similarity and variability between i) intact and stressed as wel
Like
Comment
Share
