In this paper we present a method for clustering SAGE (Serial Analysis of Gene Expression) data to detect similarities and dissimilarities between different types of cancer on the...
Abstract. This paper elaborates on an efficient approach for clustering discrete data by incrementally building multinomial mixture models through likelihood maximization using the...
In the past decades, many clustering algorithms have been proposed for the analysis of gene expression data, but little guidance is available to help choose among them. Given the ...
Abstract. Clustering has become an increasingly important task in modern application domains such as marketing and purchasing assistance, multimedia, molecular biology as well as m...
Eshref Januzaj, Hans-Peter Kriegel, Martin Pfeifle
We propose a new formulation of the clustering problem that differs from previous work in several aspects. First, the goal is to explicitly output a collection of simple and meani...