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

Author

Gypas, Foivos ; Bei, Ekaterini S. ; Zervakis, Michalis ; Sfakianakis, Stelios

Author_Institution

Dept. of Electron. & Comput. Eng., Tech. Univ. of Crete, Chania, Greece

fYear

2011

fDate

Aug. 30 2011-Sept. 3 2011

Firstpage

5551

Lastpage

5554

Abstract

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.

Keywords

biological organs; cancer; genetics; gynaecology; lab-on-a-chip; medical computing; multilayer perceptrons; ERRFI1 gene; FSMLP computational algorithm; Lasso computational algorithm; RFE-LNW computational algorithm; biomarker; breast cancer disease; breast cancer microarray dataset; computational algorithms; disease annotation; gene signature; prognostic signature; Accuracy; Breast cancer; Diseases; Logic gates; Proteins; Support vector machines; Algorithms; Breast Neoplasms; Female; Gene Expression Profiling; Humans; Neoplasm Proteins; Protein Array Analysis; Reproducibility of Results; Sensitivity and Specificity; Tumor Markers, Biological;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE

Conference_Location

Boston, MA

ISSN

1557-170X

Print_ISBN

978-1-4244-4121-1

Electronic_ISBN

1557-170X

Type

conf

DOI

10.1109/IEMBS.2011.6091416

Filename

6091416