Principal Component Analysis (PCA) is a technology for simplified analysis of data sets. PCA uses variance decomposition to reduce the dimensionality of multi-dimensional data, remove noise and redundancy, and reveal the most important elements and structures hidden behind complex data. In the field of life sciences, in proteomics and metabolomics research applications, it is usually necessary...
Evolutionary analysis can reveal the genetic sequence relationship of classification in the evolution process from the perspective of molecular evolution. In the process of biological information analysis, phylogenetic trees are often used to present the analysis results. The phylogenetic tree can reveal the biological evolution process and mechanism of related species or genes. The...
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