Validation and discovery of genotype-phenotype associations in chronic diseases using linked data

Jyotishman Pathak, Richard Kiefer, Robert Freimuth, Christopher Chute

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

This study investigates federated SPARQL queries over Linked Open Data (LOD) in the Semantic Web to validate existing, and potentially discover new genotype-phenotype associations from public datasets. In particular, we report our preliminary findings for identifying such associations for commonly occurring chronic diseases using the Online Mendelian Inheritance in Man (OMIM) and Database for SNPs (dbSNP) within the LOD knowledgebase and compare them with Gene Wiki for coverage and completeness. Our results indicate that Semantic Web technologies can play an important role for in-silico identification of novel disease-gene-SNP associations, although additional verification is required before such information can be applied and used effectively.

Original languageEnglish (US)
Title of host publicationQuality of Life Through Quality of Information - Proceedings of MIE 2012
PublisherIOS Press
Pages549-553
Number of pages5
ISBN (Print)9781614991007
DOIs
StatePublished - Jan 1 2012
Event24th Medical Informatics in Europe Conference, MIE 2012 - Pisa, Italy
Duration: Aug 26 2012Aug 29 2012

Publication series

NameStudies in Health Technology and Informatics
Volume180
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Other

Other24th Medical Informatics in Europe Conference, MIE 2012
CountryItaly
CityPisa
Period8/26/128/29/12

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Keywords

  • Genotype-phenotype associations
  • Linked Data
  • Semantic Wikis

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

Cite this

Pathak, J., Kiefer, R., Freimuth, R., & Chute, C. (2012). Validation and discovery of genotype-phenotype associations in chronic diseases using linked data. In Quality of Life Through Quality of Information - Proceedings of MIE 2012 (pp. 549-553). (Studies in Health Technology and Informatics; Vol. 180). IOS Press. https://doi.org/10.3233/978-1-61499-101-4-549