Background: Hierarchical clustering is a widely applied tool in the analysis of microarray gene expression data. The assessment of cluster stability is a major challenge in cluste...
Background: The availability of microarrays measuring thousands of genes simultaneously across hundreds of biological conditions represents an opportunity to understand both indiv...
Curtis Huttenhower, Avi I. Flamholz, Jessica N. La...
Model-based clustering exploits finite mixture models for detecting group in a data set. It provides a sound statistical framework which can address some important issues, such as...
Classical clustering algorithms are based on the concept that a cluster center is a single point. Clusters which are not compact around a single point are not candidates for class...
The problem of determining the appropriate number of components is important in finite mixture modeling for pattern classification. This paper considers the application of an unsu...