Supporting genotype-to-phenotype association studies with grid-enabled knowledge discovery workflows

Lefteris Koumakis; Vassilis Moustakis; Manolis Tsiknakis; Dimitris Kafetzopoulos; George Potamias

doi:10.1109/IEMBS.2009.5333882

Supporting genotype-to-phenotype association studies with grid-enabled knowledge discovery workflows

Annu Int Conf IEEE Eng Med Biol Soc. 2009:2009:6958-62. doi: 10.1109/IEMBS.2009.5333882.

Authors

Lefteris Koumakis¹, Vassilis Moustakis, Manolis Tsiknakis, Dimitris Kafetzopoulos, George Potamias

Affiliation

¹ Institute of Computer Science, FORTH, N. Plastira 100, 70013 Heraklion, Crete, Greece. koumakis@ics.foth.gr

PMID: 19964717
DOI: 10.1109/IEMBS.2009.5333882

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.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Biomedical Engineering
Breast Neoplasms / genetics
Computational Biology
Database Management Systems
Databases, Nucleic Acid
Female
Genetic Association Studies / statistics & numerical data*
Humans
Internet
Polymorphism, Single Nucleotide
Systems Integration