DocumentCode
2399366
Title
Supporting genotype-to-phenotype association studies with grid-enabled knowledge discovery workflows
Author
Koumakis, Lefteris ; Moustakis, Vassilis ; Tsiknakis, Manolis ; Kafetzopoulos, Dimitris ; Potamias, George
Author_Institution
Inst. of Comput. Sci., FORTH, Heraklion, Greece
fYear
2009
fDate
3-6 Sept. 2009
Firstpage
6958
Lastpage
6962
Abstract
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.
Keywords
Web services; biology computing; genomics; breast cancer; custom-made Web services; data mining; genotype-to-phenotype association; grid-enabled genotype-to-phenotype discovery scenario; grid-enabled knowledge discovery workflows; grid-enabled scientific workflows; Biomedical Engineering; Breast Neoplasms; Computational Biology; Database Management Systems; Databases, Nucleic Acid; Female; Genetic Association Studies; Humans; Internet; Polymorphism, Single Nucleotide; Systems Integration;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
Conference_Location
Minneapolis, MN
ISSN
1557-170X
Print_ISBN
978-1-4244-3296-7
Electronic_ISBN
1557-170X
Type
conf
DOI
10.1109/IEMBS.2009.5333882
Filename
5333882
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