We concatenated the expression data of the 1106 genes (left after pruning based coefficient of variation (CV) cut-off of 0.02) and computed the Euclidean distance between each pair of brain regions. Next, hierarchical clustering was performed on the distance matrix revealing the order of similarity. (TIFF)</p
When applying hierarchical clustering algorithms to cluster patient samples from microarray data, th...
<p>Hierarchical clustering was performed using gene expression data of 597 differentially expressed ...
<p>(A) Similarities between samples based on Principal Component Analysis. Expression of 82 genes li...
<p>All samples, except the ones from brain, are placed into separate subclusters per tissue. The clu...
The graphical representation showed that the profiles of gene expression were grouped into two disti...
<p>Annotated differentially expressed genes with a muscle fold change above 1.5 were clustered based...
<p>Clustering was performed by using Spearman (columns) and Euclidean (rows) distance and average li...
Micro arrays are used to assess the transcriptome of many biological systems that has generated an e...
<p>The gene list of each GO term clustered using DAVID was compared to calculate the distance betwee...
<p>Hierarchically clustered biological and technical replicates of the transcriptome data using the ...
<p>The hierarchy was created using hierarchical clustering: for each tissue, the mean expression of ...
<p>A) By gene expression of defense response genes, B) by isoform expression of two isoform genes. D...
Two-way hierarchical clustering using Ward's minimum variance as the heuristic criteria and Euclidea...
Hierarchical clustering is a commonly used and valuable approach in clustering analysis. However it ...
<p>Samples were clustered based on the similarity of their protein expression profiles observed in l...
When applying hierarchical clustering algorithms to cluster patient samples from microarray data, th...
<p>Hierarchical clustering was performed using gene expression data of 597 differentially expressed ...
<p>(A) Similarities between samples based on Principal Component Analysis. Expression of 82 genes li...
<p>All samples, except the ones from brain, are placed into separate subclusters per tissue. The clu...
The graphical representation showed that the profiles of gene expression were grouped into two disti...
<p>Annotated differentially expressed genes with a muscle fold change above 1.5 were clustered based...
<p>Clustering was performed by using Spearman (columns) and Euclidean (rows) distance and average li...
Micro arrays are used to assess the transcriptome of many biological systems that has generated an e...
<p>The gene list of each GO term clustered using DAVID was compared to calculate the distance betwee...
<p>Hierarchically clustered biological and technical replicates of the transcriptome data using the ...
<p>The hierarchy was created using hierarchical clustering: for each tissue, the mean expression of ...
<p>A) By gene expression of defense response genes, B) by isoform expression of two isoform genes. D...
Two-way hierarchical clustering using Ward's minimum variance as the heuristic criteria and Euclidea...
Hierarchical clustering is a commonly used and valuable approach in clustering analysis. However it ...
<p>Samples were clustered based on the similarity of their protein expression profiles observed in l...
When applying hierarchical clustering algorithms to cluster patient samples from microarray data, th...
<p>Hierarchical clustering was performed using gene expression data of 597 differentially expressed ...
<p>(A) Similarities between samples based on Principal Component Analysis. Expression of 82 genes li...