ArticleJournal of biomedical semantics2012
Applying semantic web technologies for phenome-wide scan using an electronic health record linked Biobank.
Article in Journal of biomedical semantics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed.
- Uncovering Important Diagnostic Features for Alzheimer's, Parkinson's and Other Dementias Using Interpretable Association Mining Methods.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2025Article
- Defining Phenotypes from Clinical Data to Drive Genomic Research.Annual review of biomedical data science · 2018Article
- Harnessing Big Data for Systems Pharmacology.Annual review of pharmacology and toxicology · 2017Review
- Methods for enhancing the reproducibility of biomedical research findings using electronic health records.BioData mining · 2017Review
- Extending XNAT Platform with an Incremental Semantic Framework.Frontiers in neuroinformatics · 2017Article
- Phenome-Wide Association Studies as a Tool to Advance Precision Medicine.Annual review of genomics and human genetics · 2016Review
- Electronic Health Records: Then, Now, and in the Future.Yearbook of medical informatics · 2016Review
- A Querying Method over RDF-ized Health Level Seven v2.5 Messages Using Life Science Knowledge Resources.JMIR medical informatics · 2016Article
- A novel framework for assessing metadata quality in epidemiological and public health research settings.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2016Article
- The role of ontologies in biological and biomedical research: a functional perspective.Briefings in bioinformatics · 2015Article
- The semantic web in translational medicine: current applications and future directions.Briefings in bioinformatics · 2015Review
- Mining Electronic Health Records using Linked Data.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2015Article
- Empowering Personalized Medicine with Big Data and Semantic Web Technology: Promises, Challenges, and Use Cases.Proceedings : ... IEEE International Conference on Big Data. IEEE International Conference on Big Data · 2014Article
- Desiderata for an authoritative Representation of MeSH in RDF.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2014Article
- Biobanking across the phenome - at the center of chronic disease research.BMC public health · 2013Article
- Developing a semantically rich ontology for the biobank-administration domain.Journal of biomedical semantics · 2013Article
- Phenome-wide association studies on a quantitative trait: application to TPMT enzyme activity and thiopurine therapy in pharmacogenomics.PLoS computational biology · 2013Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
unlabelled
backgroundThe ability to conduct genome-wide association studies (GWAS) has enabled new exploration of how genetic variations contribute to health and disease etiology. However, historically GWAS have been limited by inadequate sample size due to associated costs for genotyping and phenotyping of study subjects. This has prompted several academic medical centers to form "biobanks" where biospecimens linked to personal health information, typically in electronic health records (EHRs), are collected and stored on a large number of subjects. This provides tremendous opportunities to discover novel genotype-phenotype associations and foster hypotheses generation.
resultsIn this work, we study how emerging Semantic Web technologies can be applied in conjunction with clinical and genotype data stored at the Mayo Clinic Biobank to mine the phenotype data for genetic associations. In particular, we demonstrate the role of using Resource Description Framework (RDF) for representing EHR diagnoses and procedure data, and enable federated querying via standardized Web protocols to identify subjects genotyped for Type 2 Diabetes and Hypothyroidism to discover gene-disease associations. Our study highlights the potential of Web-scale data federation techniques to execute complex queries.
conclusionsThis study demonstrates how Semantic Web technologies can be applied in conjunction with clinical data stored in EHRs to accurately identify subjects with specific diseases and phenotypes, and identify genotype-phenotype associations.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.