Abstract
The precise diagnosis of cancer type based on microarray data is of particular importance and is also a challenging task. We have devised a novel pattern recognition procedure based on independent component analysis (ICA). Different from the conventional cancer classification methods, which are limited in their clinical applicability of cancer diagnosis, our method extracts explicitly, by ICA algorithm, a set of specific diagnostic patterns of normal and tumor tissues corresponding to a set of biomarkers for clinical use. We validated our procedure with the colon and prostate cancer data sets and achieved good diagnosis (>90%) on the data sets studied here. This technique is also suitable for the identification of diagnostic expression patterns for other human cancers and demonstrates the feasibility of simple and accurate molecular cancer diagnostics for clinical implementation.
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We thank the Hong Kong Innovation and Technology Fund BIOSUPPORT program for supporting the present research.
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Supplementary Information accompanies the paper on European Journal of Human Genetics website (http://www.nature.com/ejhg)
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Zhang, X., Yap, Y., Wei, D. et al. Molecular diagnosis of human cancer type by gene expression profiles and independent component analysis. Eur J Hum Genet 13, 1303–1311 (2005). https://doi.org/10.1038/sj.ejhg.5201495
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DOI: https://doi.org/10.1038/sj.ejhg.5201495
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