Institutional Repository
Technical University of Crete
Technical University of Crete
EN
|
EL
| URI: | http://purl.tuc.gr/dl/dias/89F47754-507F-42A9-891B-219AB7B3AE4F | ||
| Year | 2009 | ||
| Type of Item | Conference Full Paper | ||
| License |
|
||
| Bibliographic Citation | L. Koumakis, V. Moustakis, M. Tsiknakis, D. Kafetzopoulos, and D. Potamias, "Supporting Genotype‐to‐Phenotype Association Studies with Grid‐enabled Knowledge Discovery Workflows" in 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, 2009, pp. 6958-62. doi: 10.1109/IEMBS.2009.5333882. https://doi.org/10.1109/IEMBS.2009.5333882 | ||
| Appears in Collections |
Web Services and Grid-enabled scientific workflows are of paramount importance for the realization of efficient and secure knowledge discovery scenarios. This paper presents a Grid-enabled Genotype-to-Phenotype discovery scenario (GG2P), which is realized by a respective scientific workflow. GG2P supports the seamless integration of SNP genotype data sources, and the discovery of indicative and predictive genotype-to-phenotype association models - all wrapped around custom-made Web Services. GG2P is applied on a whole-genome SNP-genotyping experiment (breast cancer vs. normal/control phenotypes). A set of about 100 indicative SNPs are induced with very high classification performance. The biological relevance of the findings is supported by the relevant literature.
Copyright © DIAS 2013
