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Mapping to Ontologies Nigam Shah

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Presentation on theme: "Mapping to Ontologies Nigam Shah"— Presentation transcript:

1 Mapping to Ontologies Nigam Shah nigam@stanford.edu

2 NCBO: Key activities We create and maintain a library of biomedical ontologies. We build tools and Web services to enable the use of ontologies and their derivatives. We collaborate with scientific communities that develop and use ontologies.

3 www.bioontology.org

4 Total Monthly Visits to BioPortal

5 http://rest.bioontology.org Ontology Services Download Traverse Search Comment Download Traverse Search Comment Widgets Tree-view Auto-complete Graph-view Tree-view Auto-complete Graph-view Annotation Data Access Mapping Services Create Download Upload Create Download Upload Views Term recognition Fetch “data” annotated with a given term http://bioportal.bioontology.org

6 Mappings Root Term-1 Term-2 Term-3 Term-4 Term-5 R t1 t2 t4 t5 t6 t7 t3 Term-2 t1 Term-5 t5 Ontology A Upload or Download mapping subsets Ontology B

7 Annotation as a Web service Process textual metadata to automatically tag text with as many ontology terms as possible.

8 Code Annotator service Multiple ways to access Specific UI Excel 98 million calls, ~900 GB of data Elsevier UIMA platform

9 ANNOTATION ANALYTICS - I Analysis of semantically tagged data

10 Mining Annotations of Grants, Publications Grants from 1972 to 2007 30 funding agencies Publications from Medline Only “Journal articles”

11 BioPortal + Protégé are tools for collaborative, shared development of such hierarchies (ontologies).

12 Degree of Sponsorship

13 Allocation of Funding

14 Who funds what

15 15 Credits Mark Musen, PI The team @ www.bioontology.org/project-team NIH Roadmap grant U54 HG004028 Credits Mark Musen, PI The team @ www.bioontology.org/project-team NIH Roadmap grant U54 HG004028

16 ANNOTATION ANALYTICS - II Analysis of semantically tagged data

17 Term – 1 : Term – n Syntactic types Frequency Term recognition tool NCBO Annotator NegEx Patterns NegEx Rules – Negation detection P1ICD9 P1T1, T2, no T4 …T5, T4, T3 …T4, T3, T1 T8, T9, T4 …T6, T8, T10 T1, T2, no T4 P2 P3 : : Pn Terms form a temporal series of tags  Cohort of Interest Diseases Procedures Drugs BioPortal – knowledge graph Creating clean lexicons Annotation Workflow Further Analysis Text clinical note Terms Recognized Negation detection Generation of tagged data

18 ROR of 2.058, CI of [1.804, 2.349] PRR of 1.828, CI of [1.645, 2.032] The uncorrected X 2 statistic has p-value < 10 -7. ROR=1.524, CI=[0.872, 2.666] PRR=1.508, CI=[0.8768, 2.594] X 2 p-value=0.06816. Adverse drug events


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