Background: Inferring cluster structure in microarray datasets is a fundamental task for the so-called -omic sciences. It is also a fundamental question in Statistics, Data Analys...
Clustering large data sets of high dimensionality has always been a serious challenge for clustering algorithms. Many recently developed clustering algorithms have attempted to ad...
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
Estimating the optimal number of clusters for a dataset is one of the most essential issues in cluster analysis. An improper pre-selection for the number of clusters might easily ...
Abstract. Information networks, such as social networks and that extracted from bibliographic data, are changing dynamically over time. It is crucial to discover time-evolving comm...