In recent years, there has been a growing interest in applying Bayesian networks and their extensions to reconstruct regulatory networks from gene expression data. Since the gene ...
Identification of those genes that might anticipate the clinical behavior of different types of cancers is challenging due to availability of a smaller number of patient samples...
The k-means algorithm is widely used for clustering because of its computational efficiency. Given n points in d-dimensional space and the number of desired clusters k, k-means see...
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. Software clustering techniques are useful for extracting architectural information about a system directly from its source code structure. This paper starts by examining ...