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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Sfakianakis, S. Zervakis, M. Tsiknakis, M. Kafetzopoulos, D. |
| Copyright Year | 2010 |
| Description | Author affiliation: Institute of Molecular Biology, Foundation for Research and Technology, Heraklion 71110, Greece (Kafetzopoulos, D.) || Department of Electronic and Computer Engineering, Technical University of Crete, Chania 73100, Greece (Zervakis, M.) || Institute of Computer Science, Foundation for Research and Technology, Heraklion 71110, Greece (Sfakianakis, S.; Tsiknakis, M.) |
| Abstract | 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. |
| Starting Page | 1 |
| Ending Page | 4 |
| File Size | 211104 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424465590 |
| e-ISBN | 9781424465613 |
| DOI | 10.1109/ITAB.2010.5687658 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-11-03 |
| Publisher Place | Greece |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Bioinformatics Clustering algorithms Genomics Classification algorithms Variable speed drives Biological system modeling |
| Content Type | Text |
| Resource Type | Article |
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