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Ιδρυματικό Αποθετήριο [SANDBOX]
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| URI | http://purl.tuc.gr/dl/dias/C3EDCB9E-77F2-4F49-93CF-B9491CA3B6DF | - |
| Αναγνωριστικό | https://doi.org/10.1109/JBHI.2013.2274643 | - |
| Αναγνωριστικό | https://ieeexplore.ieee.org/document/6567891/?tp=&arnumber=6567891&url=http:%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D6567891 | - |
| Γλώσσα | en | - |
| Μέγεθος | 12 pages | en |
| Τίτλος | Nonparametric network design and analysis of disease genes in oral cancer progression | en |
| Δημιουργός | Zervakis Michail | en |
| Δημιουργός | Ζερβακης Μιχαηλ | el |
| Δημιουργός | Exarchos Konstantinos P. | en |
| Δημιουργός | Fotiadis, Dimitrios Ioannou | en |
| Δημιουργός | Bei Aikaterini | en |
| Δημιουργός | Μπεη Αικατερινη | el |
| Δημιουργός | Garofalakis Minos | en |
| Δημιουργός | Γαροφαλακης Μινως | el |
| Δημιουργός | Kalantzaki Kalliopi | en |
| Δημιουργός | Καλαντζακη Καλλιοπη | el |
| Εκδότης | Institute of Electrical and Electronics Engineers | en |
| Περίληψη | Biological 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 |
| Τύπος | Peer-Reviewed Journal Publication | en |
| Τύπος | Δημοσίευση σε Περιοδικό με Κριτές | el |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
| Ημερομηνία | 2015-10-24 | - |
| Ημερομηνία Δημοσίευσης | 2014 | - |
| Θεματική Κατηγορία | Gene network construction | en |
| Θεματική Κατηγορία | KDE | en |
| Θεματική Κατηγορία | Kernel Density Estimation | en |
| Θεματική Κατηγορία | Oral cancer | en |
| Θεματική Κατηγορία | Partial correlation | en |
| Θεματική Κατηγορία | PC | en |
| Βιβλιογραφική Αναφορά | K. 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.2013.2274643 | en |
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