<p>(A) Biplot of principal component analysis based on variant vectors. The dots show the eight <i>B. subtilis</i> strains, and the upper left image is an enlarged image focused on the three Japanese strains located near (0, 0). The fist principal component features the non-Japanese strains, and the second principal component can be regarded as a feature to distinguish strain LaoA1 and the other non-Japanese strains. (B) Hierarchical clustering of the eight <i>B. subtilis</i> strains based on the Euclidean distance between variant scores of each strain using the furthest neighbor method. The different cluster indicates that strains have different variant score patterns. (C) Geographical location of each country.</p
<p>A) PCA analysis analyzed from total mass spectra showed intermixture and widely spreaded of all i...
(A) PCA fails to clearly distinguish grapevine morphotypes. (B) A Mapper graph using PC1 as a lens r...
<div><p>Principal components analysis (PCA) and hierarchical clustering are two of the most heavily ...
<p>The figure shows the first two principal components from PCA of HA amino acid sequences from avia...
<p>(A) Dendogram that shows similarity between the <i>G</i>. <i>vaginalis</i> isolates. The colors o...
<p>(A) Dendogram. The colors of the branches represent the three largest clusters. (B) PCA biplot. A...
Understanding the genetic structure of germplasm collections is a prerequisite for effective and eff...
Understanding the genetic structure of germplasm collections is a prerequisite for effective and eff...
<p>Plotted are the first eigen-vector versus second eigen-vector for Broad samples. Eigen-vectors ar...
<p>The color codes for each time point are shown on the top right corner. The three axes PC1, PC2, a...
<p>(A) Similarities between samples based on Principal Component Analysis. Expression of 82 genes li...
<p><i>A</i>, The PCA results are provided as two-dimensional representations based on contribution s...
Principal components analysis (PCA) and hierarchical clustering are two of the most heavily used tec...
<p>Geographical regions having similarity in patterns of spoligotypes tend to clusters together.</p
Principal components analysis (PCA) and hierarchical clustering are two of the most heavily used tec...
<p>A) PCA analysis analyzed from total mass spectra showed intermixture and widely spreaded of all i...
(A) PCA fails to clearly distinguish grapevine morphotypes. (B) A Mapper graph using PC1 as a lens r...
<div><p>Principal components analysis (PCA) and hierarchical clustering are two of the most heavily ...
<p>The figure shows the first two principal components from PCA of HA amino acid sequences from avia...
<p>(A) Dendogram that shows similarity between the <i>G</i>. <i>vaginalis</i> isolates. The colors o...
<p>(A) Dendogram. The colors of the branches represent the three largest clusters. (B) PCA biplot. A...
Understanding the genetic structure of germplasm collections is a prerequisite for effective and eff...
Understanding the genetic structure of germplasm collections is a prerequisite for effective and eff...
<p>Plotted are the first eigen-vector versus second eigen-vector for Broad samples. Eigen-vectors ar...
<p>The color codes for each time point are shown on the top right corner. The three axes PC1, PC2, a...
<p>(A) Similarities between samples based on Principal Component Analysis. Expression of 82 genes li...
<p><i>A</i>, The PCA results are provided as two-dimensional representations based on contribution s...
Principal components analysis (PCA) and hierarchical clustering are two of the most heavily used tec...
<p>Geographical regions having similarity in patterns of spoligotypes tend to clusters together.</p
Principal components analysis (PCA) and hierarchical clustering are two of the most heavily used tec...
<p>A) PCA analysis analyzed from total mass spectra showed intermixture and widely spreaded of all i...
(A) PCA fails to clearly distinguish grapevine morphotypes. (B) A Mapper graph using PC1 as a lens r...
<div><p>Principal components analysis (PCA) and hierarchical clustering are two of the most heavily ...