In [1], the authors proposed a framework for automated clustering and visualization of biological data sets named AUTO-HDS. This letter is intended to complement that framework by showing that it is possible to get rid of a userdefined parameter in a way that the clustering stage can be implemented more accurately while having reduced computational complexity
This paper presents a case study to show the competence of our evolutionary and visual framework for...
We describe the use of a binary hierarchical clustering (BHC) framework for clustering of gene expre...
While a genuine abundance of biomedical data available nowadays becomes a genuine blessing, it also ...
In [1], the authors proposed a framework for automated clustering and visualization of biological da...
In many clustering applications for bioinformatics, only part of the data clusters into one or more ...
textClustering is a useful technique that divides data points into groups, also known as clusters, s...
Clustering is a long-standing problem in computer science and is applied in virtually any scientific...
Ontologies and hierarchical clustering are both important tools in biology and medicine to study hig...
textIn classical clustering, each data point is assigned to at least one cluster. However, in many ...
Clustering is the task of organizing a set of objects into meaningful groups. These groups can be di...
Hammer B, Hasenfuss A, Schleif F-M, Villmann T, Strickert M, Seiffert U. Intuitive Clustering of Bio...
A large amount of biological data has been produced in the last years. Important knowledge can be ex...
Clustering of data is a well-researched topic in computer sciences. Many approaches have been design...
Clustering is a technique commonly used in scientific research. The task of clustering inevitably in...
Summary: LOVE, a robust, scalable latent model-based clustering method for biological discovery, can...
This paper presents a case study to show the competence of our evolutionary and visual framework for...
We describe the use of a binary hierarchical clustering (BHC) framework for clustering of gene expre...
While a genuine abundance of biomedical data available nowadays becomes a genuine blessing, it also ...
In [1], the authors proposed a framework for automated clustering and visualization of biological da...
In many clustering applications for bioinformatics, only part of the data clusters into one or more ...
textClustering is a useful technique that divides data points into groups, also known as clusters, s...
Clustering is a long-standing problem in computer science and is applied in virtually any scientific...
Ontologies and hierarchical clustering are both important tools in biology and medicine to study hig...
textIn classical clustering, each data point is assigned to at least one cluster. However, in many ...
Clustering is the task of organizing a set of objects into meaningful groups. These groups can be di...
Hammer B, Hasenfuss A, Schleif F-M, Villmann T, Strickert M, Seiffert U. Intuitive Clustering of Bio...
A large amount of biological data has been produced in the last years. Important knowledge can be ex...
Clustering of data is a well-researched topic in computer sciences. Many approaches have been design...
Clustering is a technique commonly used in scientific research. The task of clustering inevitably in...
Summary: LOVE, a robust, scalable latent model-based clustering method for biological discovery, can...
This paper presents a case study to show the competence of our evolutionary and visual framework for...
We describe the use of a binary hierarchical clustering (BHC) framework for clustering of gene expre...
While a genuine abundance of biomedical data available nowadays becomes a genuine blessing, it also ...