Clustering genomic microarrays

Figure 2.8 Microarray cross-platform showing differentially expressed gene clusters obtained from Amersham, Agilent, and Affymetrix products. (From Barczak, A., etal., Genome Res., 13, 1775-1785, 2003 [Copyright 2003 Cold Spring Harbor Laboratory Press] and Tan, P.K. etal.. Nucleic Acid Res., 31(19), 5676-5684, 2003. With permission.)...

In summary, we find gene expression profiling with microarrays to be an exceptionally powerful and profound analytical fool. Not only is the technique useful for global analyses, for example, of mefabolic pathways and their interrelationships, but it also has the ability to focus upon (albeit assisted by clustering) and track important singular events that would otherwise remain hidden under a genomic backdrop. 

Ellmark, P, Woolfson, A, Belov, L., and Christopherson, R.I. 2008. The applicability of a cluster of differentiation monoclonal antibody microarrays to the diagnosis of human disease. In Genomic Protocols, 2nd ed., M. Starkey and R. Elaswarapu, Eds., Humana Press, Totowa, NJ Meth Mol Biol 439 199-209. 

We thank Dr. Richard R. Almon and Dr. Debra C. DuBois for collaborations on genomic assays and microarray cluster analysis. This work was supported by NIH Grants GM 24211 and GM 57980. 

Sheng, Q., et al. (2005). Advances in cluster analysis of microarray data. In Data Analysis and Visualization in Genomics and Proteomics, F. Azuje and J. Dopazo, (Eds.). West Sussex, England Wiley. 

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