Tutorial: Introduction to Biomedical Ontology for Clinical and Translational Research

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April 24, 2012

10:00am Registration and Coffee

10:30am Foundations of Biomedical Ontology (Barry Smith)

What is an ontology and what is it useful for?
The problem of data silos
NIH mandates for sharing and reuse of research data
Examples of Biomedical Ontologies
  • Gene Ontology (GO)
  • Ontology for General Medical Science (OGMS)
  • Infectious Disease Ontology (IDO)
  • Mental and Neurological Disease Ontologies

12:00 pm Lunch

1:00pm The Ontology Landscape (Barry Smith and Nigam Shah)

The National Center for Biomedical Ontology (NCBO)
The Semantic Web and Linked Open Data
BioPortal SPARQL endpoint
Open Biomedical Ontologies (OBO) and the OBO Foundry

2:30pm Break

3:00pm Introduction to NCBO Technology (Nigam Shah)

(1) Web Services and BioPortal
Search service
Term services
Annotator Web Service
(2) Using NCBO Technology in your project
(3) Examples of use of NCBO services for data retrieval, integration and reasoning
Resource Index
Enrichment Analysis and http://www.ncbi.nlm.nih.gov/pubmed/21550421
(5) Examples of CTSA use cases enabled by NCBO technology
Health Ontology Mapper
Importing Ontologies into i2b2 Hive

5:30pm Close

Faculty: Barry Smith (Buffalo / NCBO) and Nigam Shah (Stanford / NCBO)

This tutorial will provide participants with an understanding of how ontologies and terminologies are used in a variety of contexts in clinical and translational research.

By the end of the tutorial, participants will be able to:

  • Understand the biomedical ontology landscape
  • Understand the national infrastructure available for data annotation and knowledge management
  • Learn about NCBO supported Web service workflows for clinical and translational research.

The National Center for Biomedical Ontology (NCBO) offers a range of Web services that allow users to access biomedical terminologies and ontologies, to use ontology terms to create pick lists and lexicons, to identify terms from controlled terminologies and ontologies that can describe and index the contents of online data sets (data annotation), and to recommend particular terminologies and ontologies that would be appropriate for data-annotation tasks. The tutorial will demonstrate the use of NCBO resources to facilitate tasks such as semantic data integration, information retrieval, structured data entry, and knowledge management. We will review example use cases for analyses using disease ontologies and for applying NCBO tools to compute the risk of having a myocardial infarction on taking Vioxx (rofecoxib) for Rheumatoid arthritis.