Knowledgeable clustering of microarray data

Abstract

A novel graph-theoretic clustering (GTC) is presented. The method relies on a weighted graph arrangement of the genes, and the iterative partitioning of the respective minimum spanning tree of the graph. The final result is the hierarchical clustering of the genes. GTC utilizes information about the functional classification of genes to knowledgeably guide the clustering process and achieve more informative clustering results. The method was applied and tested on an indicative real-world domain producing satisfactory and biologically valid results. Future R&D directions are also posted. © Springer-Verlag Berlin Heidelberg 2004.