Institutional Repository
Technical University of Crete
Technical University of Crete
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EL
| URI: | http://purl.tuc.gr/dl/dias/3FE7265F-EE92-45AA-906E-CECB8D2852EE | ||
| Year | 2011 | ||
| Type of Item | Peer-Reviewed Journal Publication | ||
| License |
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| Bibliographic Citation | M. E. Blazadonakis, M. E. Zervakis and D. Kafetzopoulos, "Integration of gene signatures using biological knowledge," Artificial Intel. Med., vol. 53, no.1, pp. 57-71, Sep. 2011. doi:10.1016/j.artmed.2011.06.003 https://doi.org/10.1016/j.artmed.2011.06.003 | ||
| Appears in Collections |
Gene expression patterns that distinguish clinically significant disease subclasses may not only play a prominent role in diagnosis, but also lead to the therapeutic strategies tailoring the treatment to the particular biology of each disease. Nevertheless, gene expression signatures derived through statistical feature-extraction procedures on population datasets have received rightful criticism, since they share few genes in common, even when derived from the same dataset. We focus on knowledge complementarities conveyed by two or more gene-expression signatures by means of embedded biological processes and pathways, which alternatively form a meta-knowledge platform of analysis towards a more global, robust and powerful solution.
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