Characteristics of the 2 clusters obtained by a hierarchical cluster analysis.</p
<p>Hierarchical cluster analysis of the TF differential expressed between MT and WT.</p
<p>Dendogram corresponding to the Hierarchical cluster analysis using average between group linkage....
Viseme categories created using hierarchical cluster analysis, with minimum 70% cluster criterion.</...
Description of the most influencing qualitative variables in the selection of clusters of a hierarch...
Sample characteristics and differences of measures between three IS clusters.</p
The properties of the two clusters generated from using Markov clustering algorithm.</p
Hierarchical clustering, where final nodes are the selected groups for classification.</p
<p>Characteristics of the three clusters and the total sample (categorical variables).</p
The characteristics of the parameters after using the filtering and improved clustering algorithms.<...
<p>Characteristics of the three clusters and the total sample (continuous variables).</p
Summary of metrics for clusters obtained by weighted unifrac hierarchical analysis.</p
<p>Clusters, members, rankings and statistical characteristics of the identified top-30 ranked nodes...
Results of the clusters identified by the two-step cluster analysis for all the playing positions (I...
Number of genotypes, seed longevity (G%) and 100 seed weight (100SW) of clusters formed in hierarchi...
<p>Hierarchical cluster analysis based on percentages of modal characteristics of structural dimensi...
<p>Hierarchical cluster analysis of the TF differential expressed between MT and WT.</p
<p>Dendogram corresponding to the Hierarchical cluster analysis using average between group linkage....
Viseme categories created using hierarchical cluster analysis, with minimum 70% cluster criterion.</...
Description of the most influencing qualitative variables in the selection of clusters of a hierarch...
Sample characteristics and differences of measures between three IS clusters.</p
The properties of the two clusters generated from using Markov clustering algorithm.</p
Hierarchical clustering, where final nodes are the selected groups for classification.</p
<p>Characteristics of the three clusters and the total sample (categorical variables).</p
The characteristics of the parameters after using the filtering and improved clustering algorithms.<...
<p>Characteristics of the three clusters and the total sample (continuous variables).</p
Summary of metrics for clusters obtained by weighted unifrac hierarchical analysis.</p
<p>Clusters, members, rankings and statistical characteristics of the identified top-30 ranked nodes...
Results of the clusters identified by the two-step cluster analysis for all the playing positions (I...
Number of genotypes, seed longevity (G%) and 100 seed weight (100SW) of clusters formed in hierarchi...
<p>Hierarchical cluster analysis based on percentages of modal characteristics of structural dimensi...
<p>Hierarchical cluster analysis of the TF differential expressed between MT and WT.</p
<p>Dendogram corresponding to the Hierarchical cluster analysis using average between group linkage....
Viseme categories created using hierarchical cluster analysis, with minimum 70% cluster criterion.</...
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