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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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URIhttp://purl.tuc.gr/dl/dias/5244C116-7CF3-4ED6-8213-921693587936-
Identifierhttps://doi.org/10.1109/IEMBS.2011.6091416-
Identifierhttps://ieeexplore.ieee.org/document/6091416/-
Languageen-
Extent4 pagesen
TitleA disease annotation study of gene signatures in a breast cancer microarray dataseten
CreatorZervakis Michailen
CreatorΖερβακης Μιχαηλel
CreatorSfakianakis Stylianosen
CreatorΣφακιανακης Στυλιανοςel
CreatorGypas Foivosen
CreatorBei Aikaterinien
CreatorΜπεη Αικατερινηel
PublisherInstitute of Electrical and Electronics Engineersen
Content SummaryBreast 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. en
Type of ItemΠλήρης Δημοσίευση σε Συνέδριοel
Type of ItemConference Full Paperen
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-10-25-
Date of Publication2011-
SubjectBreast canceren
SubjectDiseasesen
SubjectSupport vector machinesen
SubjectLogic gatesen
SubjectAccuracyen
SubjectProteinsen
Bibliographic CitationF. 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.2011.6091416en

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