SNP-Converter: an Ontology-Based solution to Reconcile Heterogeneous SNP Descriptions for Pharmacogenomic Studies

Adrien Coulet (1, 2) , Malika Smaïl-Tabbone (1) , Pascale Benlian (3) , Amedeo Napoli (1) , Marie-Dominique Devignes (1)

1 ORPAILLEUR - Knowledge representation, reasonning
2 KIKA MEDICAL - KIKA medical
3 Trafic Membranaire et Signalisation Dans les Cellules Epitheliales

Pharmacogenomics explores the impact of individual genomic variations in health problems such as adverse drug reactions. Records of millions of genomic variations, mostly known as Single Nucleotide Polymorphisms (SNP), are available today in various overlapping and heterogeneous databases. Selecting and extracting from these databases or from private sources a proper set of polymorphisms are the first steps of a KDD (Knowledge Discovery in Databases) process in pharmacogenomics. It is however a tedious task hampered by the heterogeneity of SNP nomenclatures and annotations. Standards for representing genomic variants have been proposed by the Human Genome Variation Society (HGVS). The SNP-Converter application is aimed at converting any SNP description into an HGVS-compliant pivot description and vice versa. Used in the frame of a knowledge system, the SNP-Converter application contributes as a wrapper to semantic data integration and enrichment.

Domaines: Intelligence artificielle [cs.AI]; Base de données [cs.DB]; Bio-Informatique, Biologie Systémique [q-bio.QM]

Adrien Coulet, Malika Smaïl-Tabbone, Pascale Benlian, Amedeo Napoli, Marie-Dominique Devignes. SNP-Converter: an Ontology-Based solution to Reconcile Heterogeneous SNP Descriptions for Pharmacogenomic Studies. 3rd International Workshop on Data Integration in the Life Sciences 2006 - DILS'06, Jul 2006, European Bioinformatics Institute (EBI), Hinxton/UK. ⟨inria-00080050⟩