<p>Cancer samples and normal donor samples (brackets) were clustered using a hierarchical clustering program to show sample-to-sample relationships. Sample labels include donor condition (cancer type or normal), sample lot number (last three digits), gender, and cancer stage (2 – 4, or 0 for normal). Labels marked with a or b indicate repeat testing of the same sample.</p
<p>A green-red heat map was used to visualize the clustering results. As illustrated, luminal type B...
<p>Hierarchical clustering analysis of a random subset of human microbiome samples taken from five h...
<p>(A) Hierarchical clustering of primary tumors reveals three distinct classes (B) Kaplan–Meier met...
<p>(A) Unsupervised hierarchical clustering (UHCL) for 22 LMS and 22 UPS revealed two global cluster...
When applying hierarchical clustering algorithms to cluster patient samples from microarray data, th...
<p>Hierarchical clustering of 183 breast tumor samples using the 500 most variant genes across all s...
<p>Dendrogram for clustering experiments was created using centred correlation and average linkage m...
When applying hierarchical clustering algorithms to cluster patient samples from microarray data, th...
<p>The letter C represented cancer, and N represented normal. Red was hypermethylation, white is mid...
<p>The patients were grouped according to the menstrual cycle phase (proliferative and secretory), n...
Clustering algorithms are extensively used on patient tissue samples in order to group and visualize...
<p>Hierarchical clustering was generated using R 2.14.1. The method used to compute the distance was...
<p>a) Clustering based on GSE4554 and b) Clustering based on the four largest batches of the TCGA RN...
<p><b>Copyright information:</b></p><p>Taken from "The influence of tumor size and environment on ge...
<p>Hierarchical clustering of the ComBat-merged MPH dataset recreates clear normal-like, fibroprolif...
<p>A green-red heat map was used to visualize the clustering results. As illustrated, luminal type B...
<p>Hierarchical clustering analysis of a random subset of human microbiome samples taken from five h...
<p>(A) Hierarchical clustering of primary tumors reveals three distinct classes (B) Kaplan–Meier met...
<p>(A) Unsupervised hierarchical clustering (UHCL) for 22 LMS and 22 UPS revealed two global cluster...
When applying hierarchical clustering algorithms to cluster patient samples from microarray data, th...
<p>Hierarchical clustering of 183 breast tumor samples using the 500 most variant genes across all s...
<p>Dendrogram for clustering experiments was created using centred correlation and average linkage m...
When applying hierarchical clustering algorithms to cluster patient samples from microarray data, th...
<p>The letter C represented cancer, and N represented normal. Red was hypermethylation, white is mid...
<p>The patients were grouped according to the menstrual cycle phase (proliferative and secretory), n...
Clustering algorithms are extensively used on patient tissue samples in order to group and visualize...
<p>Hierarchical clustering was generated using R 2.14.1. The method used to compute the distance was...
<p>a) Clustering based on GSE4554 and b) Clustering based on the four largest batches of the TCGA RN...
<p><b>Copyright information:</b></p><p>Taken from "The influence of tumor size and environment on ge...
<p>Hierarchical clustering of the ComBat-merged MPH dataset recreates clear normal-like, fibroprolif...
<p>A green-red heat map was used to visualize the clustering results. As illustrated, luminal type B...
<p>Hierarchical clustering analysis of a random subset of human microbiome samples taken from five h...
<p>(A) Hierarchical clustering of primary tumors reveals three distinct classes (B) Kaplan–Meier met...