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Revealing disease mechanisms via coupling molecular pathways scaffolds and microarrays: Astudy on the wilm’s tumor disease

George Potamias, Dimitris Kafetzopoulos, Alexandros Kanterakis, Alexandros Kanterakis

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URI: http://purl.tuc.gr/dl/dias/2F4B387F-261A-4563-9AA4-66D17226031E
Year 2009
Type of Item Conference Full Paper
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Bibliographic Citation Α. Kanterakis, V. Moustakis, D. Kafetzopoulos, G. Potamias. (2009). Revealing Disease Mechanisms via Coupling Molecular Pathways Scaffolds and Microarrays: A Study on the Wilm’s Tumor Disease. Presented at Biomedical Informatics and Intelligent Methods in the support of Genomic Medicine, Workshop – Artificial Intelligence Applications and Innovations International Conference. [Online]. Available: http://www.researchgate.net/publication/220828442_Revealing_Disease_Mechanisms_via_Coupling_Molecular_Path
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Summary

Moving towards the realization of genomic data in clinical practice, and following an individualized healthcare approach, the function and regulation of genes has to be deciphered and manifested. This is even more possible after the later advances in the area of molecular biology and biotechnology that have brought vast amount of invaluable data to the disposal of researchers. Two of the most significant forms of data come form microarray gene expression sources, and gene interactions sources - as encoded in Gene Regulatory Pathways (GRPs). The usual computational task involving microarray experiments is the gene selection procedure while, GRPs are used mainly for data annotation. In this study we present a novel perception of these resources. Initially we locate all functional paths encoded in GRPs and we try to assess which of them are compatible with the gene-expression values of samples that belong to different clinical categories (diseases and phenotypes). Then we apply usual feature selection techniques to identify the paths that discriminate between the different clinical phenotypes providing a paradigm shift over the usual gene selection approaches. The differential ability of the selected paths is evaluated and their biological relevance is assessed. The whole approach was applied on the Wilm's tumor domain with very good and indicative results.

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