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A disease annotation study of gene signatures in a breast cancer microarray dataset

Zervakis Michail, Sfakianakis Stylianos, Gypas Foivos, Bei Aikaterini

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URI: http://purl.tuc.gr/dl/dias/5244C116-7CF3-4ED6-8213-921693587936
Year 2011
Type of Item Conference Full Paper
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Bibliographic Citation F. Gypas, E. S. Bei, M. Zervakis and S. Sfakianakis, "A disease annotation study of gene signatures in a breast cancer microarray dataset," in Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011, pp. 5551-5554. doi: 10.1109/IEMBS.2011.6091416 https://doi.org/10.1109/IEMBS.2011.6091416
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Summary

Breast cancer is a complex disease with heterogeneity between patients regarding prognosis and treatment response. Recent progress in advanced molecular biology techniques and the development of efficient methods for database mining lead to the discovery of promising novel biomarkers for prognosis and prediction of breast cancer. In this paper, we applied three computational algorithms (RFE-LNW, Lasso and FSMLP) to one microarray dataset for breast cancer and compared the obtained gene signatures with a recently described disease-agnostic tool, the Genotator. We identified a panel of 152 genes as a potential prognostic signature and the ERRFI1 gene as possible biomarker of breast cancer disease.

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