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Biclustering strategies for genetic marker selection in gynecologic tumor cell lines

Alevyzaki Androniki, Sfakianakis Stylianos, Bei Aikaterini, Obermayr Eva, Zeillinger Robert, Fotiadis D. I., Zervakis Michail

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URIhttp://purl.tuc.gr/dl/dias/1B73E0C5-1C73-41F7-A42D-2C44251C4F9E-
Αναγνωριστικόhttps://ieeexplore.ieee.org/document/7590977/-
Αναγνωριστικόhttps://doi.org/10.1109/EMBC.2016.7590977-
Γλώσσαen-
Μέγεθος4 pagesen
ΤίτλοςBiclustering strategies for genetic marker selection in gynecologic tumor cell linesen
ΔημιουργόςAlevyzaki Andronikien
ΔημιουργόςΑλεβυζακη Ανδρονικηel
ΔημιουργόςSfakianakis Stylianosen
ΔημιουργόςΣφακιανακης Στυλιανοςel
ΔημιουργόςBei Aikaterinien
ΔημιουργόςΜπεη Αικατερινηel
ΔημιουργόςObermayr Evaen
ΔημιουργόςZeillinger Roberten
ΔημιουργόςFotiadis D. I.en
ΔημιουργόςZervakis Michailen
ΔημιουργόςΖερβακης Μιχαηλel
ΕκδότηςInstitute of Electrical and Electronics Engineersen
ΠερίληψηOver the past few decades great interest has been focused on cell lines derived from tumors, because of their usability as models to understand the biology of cancer. At the same time, advanced technologies such as DNA-microarrays have been broadly used to study the expression level of thousands of genes in primary tumors or cancer cell lines in a single experiment. Results from microarray analysis approaches have provided valuable insights into the underlying biology and proven useful for tumor classification, prognostication and prediction. Our approach utilizes biclustering methods for the discovery of genes with coherent expression across a subset of conditions (cell lines of a tumor type). More specifically, we present a novel modification on Cheng & Church's algorithm that searches for differences across the studied conditions, but also enforces consistent intensity characteristics of each cluster within each condition. The application of this approach on a gynecologic panel of cell lines succeeds to derive discriminant groups of compact bi-clusters across four types of tumor cell lines. In this form, the proposed approach is proven efficient for the derivation of tumor-specific markers. en
ΤύποςΠλήρης Δημοσίευση σε Συνέδριοel
ΤύποςConference Full Paperen
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2018-10-09-
Ημερομηνία Δημοσίευσης2016-
Θεματική ΚατηγορίαGene expressionen
Θεματική ΚατηγορίαCanceren
Θεματική ΚατηγορίαTumorsen
Θεματική ΚατηγορίαClustering algorithmsen
Θεματική ΚατηγορίαArtificial intelligenceen
Θεματική ΚατηγορίαElectronic mailen
Βιβλιογραφική ΑναφοράA. Alevyzaki, S. Sfakianakis, E. S. Bei, E. Obermayr, R. Zeillinger, D. Fotiadis, M. Zervakis, "Biclustering strategies for genetic marker selection in gynecologic tumor cell lines," in 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2016, pp. 1430-1433. doi: 10.1109/EMBC.2016.7590977en

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