A Novel Clustering Approach: Global Optimum Search with Enhanced Positioning

摘要

Cluster analysis of DNA expression data is a useful tool for identifying biologically relevant gene groupings. It is hence important to apply a rigorous yet intuitive clustering algorithm to uncover these genomic relationships. Here, we describe a clustering framework [1,2] based on a variant of the Generalized Benders Decomposition, the Global Optimum Search [3,4]. We apply the proposed algorithm to experimental DNA microarray data and compare the results to that obtained with some commonly-used algorithms. We also propose an extension to iteratively uncover the optimal biologically coherent structures.