Data clustering methods have been proven to be a successful data mining technique in the analysis of gene expression data. The Cluster affinity search technique (CAST) developed b...
Abdelghani Bellaachia, David Portnoy, Yidong Chen,...
— An important consideration in clustering is the determination of the correct number of clusters and the appropriate partitioning of a given data set. In this paper, a newly dev...
Background: Detecting groups of functionally related proteins from their amino acid sequence alone has been a long-standing challenge in computational genome research. Several clu...
Tobias Wittkop, Jan Baumbach, Francisco P. Lobo, S...
Biclustering refers to simultaneously capturing correlations present among subsets of attributes (columns) and records (rows). It is widely used in data mining applications includ...
In previous work on "transformed mixtures of Gaussians" and "transformed hidden Markov models", we showed how the EM algorithm in a discrete latent variable mo...