Introduction to Bio-Ontologies and Their Applications
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- Venue: Oak Room, 2nd Floor, Tresidder Union, Stanford University, Directions.
- Date: Tutorial: March 15, 2012
- Organization: Barry Smith (NCBO / Buffalo), Trish Whetzel (NCBO / Stanford University), and Nigam Shah (NCBO / Stanford University)
- Registration: Please write to Barry Smith
- Audience: Some background in bioinformatics or medical informatics is required. No knowledge of ontology is presupposed.
- 1:00pm What is an ontology and what is it useful for? (Barry Smith)
- We will provide an introduction to biomedical ontology with a focus on the conditions for successful development and application of ontologies. Topics to be covered include:
- The reasons for the success of the Gene Ontology
- What is the difference between an ontology and a database?
- Why you should use an ontology to support your research
- 2:30pm NCBO Web Services and Development of Semantic Applications (Trish Whetzel)
- We will provide an overview of NCBO Web services and of how they are being incorporated into software applications.
- Introduction to REST Web services
- NCBO BioPortal
- NCBO REST Web services
- Ontology Web services - Search, Traverse, Download
- View Extraction Web service - Subset
- Notes Web service - Propose Terms, Comment
- Mapping Web services - Create, Upload, Download
- Widgets - Tree view, Auto-complete, Graph view
- Annotation - Ontology Term recognition
- Data Access - Fetch ontology-indexed data
- BioPortal SPARQL Endpoint - Access Ontologies via SPARQL
- 4:00pm Use of ontologies in biomedical research (Nigam Shah)
- We will review the use of NCBO components to create an annotation workflow (specifically using the Annotator and Lexicon Builder components). We will then discuss the applications of this workflow to 9.5 million clinical documents--from the electronic health records of approximately one million adult patients from the STRIDE Clinical Data Warehouse, part of Stanford's CTSA Informatics platform--to identify statistically significant patterns of drug use and to conduct drug safety surveillance.
- For the patterns of drug use, we validate the usage patterns learned from the data against FDA-approved indications as well as external sources of known off-label use such as Medi-Span. For drug safety surveillance, we show that drug–disease co-occurrences and the temporal ordering of drugs and disease mentions in clinical notes can be examined for statistical enrichment and used to detect potential adverse events.