Gene Ontology Assisted Exploratory Microarray Clustering and Its Application to Cancer

Authors:
Geoff Macintyre;James Bailey;Daniel Gustafsson;Alex Boussioutas;Izhak Haviv;Adam Kowalczyk
Affiliations:
Department of Computer Science and Software Engineering, University of Melbourne, Victoria, Australia and National ICT Australia, Victorian Research Lab, Australia;Department of Computer Science and Software Engineering, University of Melbourne, Victoria, Australia and National ICT Australia, Victorian Research Lab, Australia;Department of Computer Science and Computer Engineering, La Trobe University, Victoria, Australia;Ian Potter Centre for Cancer Genomics and Predictive Medicine, Peter MacCallum Cancer Centre, East Melbourne, Australia;The Alfred Medical Research and Education Precinct, Baker Medical Research Institute, Epigenetics Group, Melbourne, Australia and Department of Biochemistry and Molecular Biology, University of Me ...;National ICT Australia, Victorian Research Lab, Australia
Venue:
PRIB '08 Proceedings of the Third IAPR International Conference on Pattern Recognition in Bioinformatics
Year:
2008

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Abstract

Gene expression profiling provides insight into the functions of genes at a molecular level. Clustering of gene expression profiles can facilitate the identification of the underlying driving biological program causing genes' co-expression. Standard clustering methods, grouping genes based on similar expression values, fail to capture weak expression correlations potentially causing genes in the same biological process to be grouped separately. We have developed a novel clustering algorithm which incorporates functional gene information from the Gene Ontology into the clustering process, resulting in more biologically meaningfull clusters. We have validated our method using a multi-cancer microarray dataset. In addition, we show the potential of such methods for the exploration of cancer etiology.