<p>Four examples of clusters are presented; for each, a phylogram and graphical representation of the average of corrected number of instances per age and disease is illustrated. Examples were chosen for their diversity in patterns.</p
A hierarchy, characterized by tree-like relationships, is a natural method of organizing data in var...
BackgroundHierarchical cluster analysis (HCA) is a widely used classificatory technique in many area...
Abstract — Clustering techniques have a wide use and importance nowadays. This importance tends to i...
<p>On the left the hierarchical clustering of all SNP blocks associated to a particular gene. On the...
<p>Clustering results from the selected cut levels. Bilaterally symmetric clusters are displayed in ...
The objective of data mining is to take out information from large amounts of data and convert it in...
Abstract: Clustering is the assignment of data objects (records) into groups (called clusters) so th...
<p>Hierarchical clustering of the ComBat-merged MPH dataset recreates clear normal-like, fibroprolif...
<p>The total number of descriptors equals 919. They belong to 6 different categories which are as fo...
Clustering is the task of organizing a set of objects into meaningful groups. These groups can be di...
Finding clusters in a complex dataset is not straightforward. Different indices were developed to qu...
Abstract: A fundamental and difficult problem in cluster analysis is the determination of the “true...
Finding clusters in a complex dataset is not straightforward. Different indices were developed to qu...
The task of the presented study is to find different disease phenotypes of cancer (breast cancer, ca...
<p>Agglomerative hierarchical cluster analysis for the whole data set to define the natural division...
A hierarchy, characterized by tree-like relationships, is a natural method of organizing data in var...
BackgroundHierarchical cluster analysis (HCA) is a widely used classificatory technique in many area...
Abstract — Clustering techniques have a wide use and importance nowadays. This importance tends to i...
<p>On the left the hierarchical clustering of all SNP blocks associated to a particular gene. On the...
<p>Clustering results from the selected cut levels. Bilaterally symmetric clusters are displayed in ...
The objective of data mining is to take out information from large amounts of data and convert it in...
Abstract: Clustering is the assignment of data objects (records) into groups (called clusters) so th...
<p>Hierarchical clustering of the ComBat-merged MPH dataset recreates clear normal-like, fibroprolif...
<p>The total number of descriptors equals 919. They belong to 6 different categories which are as fo...
Clustering is the task of organizing a set of objects into meaningful groups. These groups can be di...
Finding clusters in a complex dataset is not straightforward. Different indices were developed to qu...
Abstract: A fundamental and difficult problem in cluster analysis is the determination of the “true...
Finding clusters in a complex dataset is not straightforward. Different indices were developed to qu...
The task of the presented study is to find different disease phenotypes of cancer (breast cancer, ca...
<p>Agglomerative hierarchical cluster analysis for the whole data set to define the natural division...
A hierarchy, characterized by tree-like relationships, is a natural method of organizing data in var...
BackgroundHierarchical cluster analysis (HCA) is a widely used classificatory technique in many area...
Abstract — Clustering techniques have a wide use and importance nowadays. This importance tends to i...
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