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Nonparametric network design and analysis of disease genes in oral cancer progression

Zervakis Michail, Exarchos Konstantinos P., Fotiadis, Dimitrios Ioannou, Bei Aikaterini, Garofalakis Minos, Kalantzaki Kalliopi

Απλή Εγγραφή


URIhttp://purl.tuc.gr/dl/dias/C3EDCB9E-77F2-4F49-93CF-B9491CA3B6DF-
Αναγνωριστικόhttps://doi.org/10.1109/JBHI.2013.2274643-
Αναγνωριστικόhttps://ieeexplore.ieee.org/document/6567891/?tp=&arnumber=6567891&url=http:%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D6567891-
Γλώσσαen-
Μέγεθος12 pagesen
ΤίτλοςNonparametric network design and analysis of disease genes in oral cancer progressionen
ΔημιουργόςZervakis Michailen
ΔημιουργόςΖερβακης Μιχαηλel
ΔημιουργόςExarchos Konstantinos P.en
ΔημιουργόςFotiadis, Dimitrios Ioannouen
ΔημιουργόςBei Aikaterinien
ΔημιουργόςΜπεη Αικατερινηel
ΔημιουργόςGarofalakis Minosen
ΔημιουργόςΓαροφαλακης Μινωςel
ΔημιουργόςKalantzaki Kalliopien
ΔημιουργόςΚαλαντζακη Καλλιοπηel
ΕκδότηςInstitute of Electrical and Electronics Engineersen
ΠερίληψηBiological networks in living organisms can be seen as the ultimate means of understanding the underlying mechanisms in complex diseases, such as oral cancer. During the last decade, many algorithms based on high-throughput genomic data have been developed to unravel the complexity of gene network construction and their progression in time. However, the small size of samples compared to the number of observed genes makes the inference of the network structure quite challenging. In this study, we propose a framework for constructing and analyzing gene networks from sparse experimental temporal data and investigate its potential in oral cancer. We use two network models based on partial correlations and kernel density estimation, in order to capture the genetic interactions. Using this network construction framework on real clinical data of the tissue and blood at different time stages, we identified common disease-related structures that may decipher the association between disease state and biological processes in oral cancer. Our study emphasizes an altered MET (hepatocyte growth factor receptor) network during oral cancer progression. In addition, we demonstrate that the functional changes of gene interactions during oral cancer progression might be particularly useful for patient categorization at the time of diagnosis and/or at follow-up periods. en
ΤύποςPeer-Reviewed Journal Publicationen
ΤύποςΔημοσίευση σε Περιοδικό με Κριτέςel
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2015-10-24-
Ημερομηνία Δημοσίευσης2014-
Θεματική ΚατηγορίαGene network constructionen
Θεματική ΚατηγορίαKDEen
Θεματική ΚατηγορίαKernel Density Estimationen
Θεματική ΚατηγορίαOral canceren
Θεματική ΚατηγορίαPartial correlationen
Θεματική ΚατηγορίαPCen
Βιβλιογραφική ΑναφοράK. Kalantzaki, E. S. Bei, K. P. Exarchos, M. Zervakis, M. Garofalakis and D. I. Fotiadis," Nonparametric network design and analysis of disease genes in oral cancer progression," IEEE J. Biomed. Health Inform., vol. 18, no.2, pp. 562-573, Mar. 2014. doi: 10.1109/JBHI.2013.2274643en

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