Supporting genotype-to-phenotype association studies with grid-enabled knowledge discovery workflows.
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.
Koumakis
Lefteris
L
Institute of Computer Science, FORTH, N. Plastira 100, 70013 Heraklion, Crete, Greece. koumakis@ics.foth.gr
Moustakis
Vassilis
V
Tsiknakis
Manolis
M
Kafetzopoulos
Dimitris
D
Potamias
George
G
D001698:Biomedical Engineering; D001943:Breast Neoplasms / Q000235:genetics; D019295:Computational Biology; D003628:Database Management Systems; D030561:Databases, Nucleic Acid; D005260:Female; D056726:Genetic Association Studies / Q000706:statistics & numerical data*; D006801:Humans; D020407:Internet; D020641:Polymorphism, Single Nucleotide; D018511:Systems Integration