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Integration of biological knowledge in the mixture-of-Gaussians analysis of genomic clustering

Dimitris Kafetzopoulos, Zervakis Michalis, Manolis Tsiknakis, Stelios Sfakianakis

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URI: http://purl.tuc.gr/dl/dias/262ED0F3-5B3A-44DA-B770-9B71FCD0F513
Έτος 2010
Τύπος Πλήρης Δημοσίευση σε Συνέδριο
Άδεια Χρήσης
Λεπτομέρειες
Βιβλιογραφική Αναφορά S. Sfakianakis, M. Zervakis, M. Tsiknakis, D. Kafetzopoulos , "Integration of biological knowledge in the mixture-of-Gaussians analysis of genomic clustering ,"in 2010 10th IEEE Intern.l Conf. on Information Tech. and Applications in Biom. (ITAB) ,pp.1-4.doi:10.1109/ITAB.2010.5687658 https://doi.org/10.1109/ITAB.2010.5687658
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Περίληψη

The analysis of biological data produced by state of the art high throughput technologies like DNA microarrays presents many challenges due both to the domain itself (e.g. high dimensionality) and the technologies themselves (e.g. noisy data). In this paper we advocate the exploitation of existing biological knowledge in order to guide the cluster analysis of gene expression data. To this end we present a biologically inspired probabilistic model and a modified Expectation-Maximization algorithm for the estimation of its parameters. Finally we perform some initial evaluation of the clustering results of the proposed model.

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