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BFO-aligned Ontologies for Clinical and Translational Research:
OGMS, IDO, and VO
(Orlando Presentation, 2/8/2013)http://ncorwiki.buffalo.edu/index.php/CTSA_Ontology_Workshop
Yongqun “Oliver” He
University of Michigan Medical SchoolAnn Arbor, MI 48109
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BFO and OBO Foundry Principles
• BFO: Basic Formal Ontology
• BFO has been used a top level ontology for many ontologies associated with clinical and translational research
• Examples: OGMS, IDO, VO, OBI, OAE
• All OBO foundry library ontologies follow OBO Foundry principles, e.g., openness, collaboration, and use of a common shared syntax
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OGMS: Ontology of General
Medical Science • An ontology of the major
types of entities involved in a clinical encounter.– An upper ontology for
clinical medicine– A mid-level ontology with
respect to BFO
• Includes ~100 general terms
• By: – Albert Goldfain – Richard Scheuermann– Barry Smith, …
https://code.google.com/p/ogms/
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Wide OGMS Applications
Ontologies using OGMS:
• IDO• DO• SDO• AERO • OAE• VSO• OMRSE• VO• ...
Courtesy: figure kindly provided by Albert Goldfain
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OGMS application example:Development of OAE
• OAE: Ontology of Adverse Events• OAE ‘adverse event’:
– = def. a OGMS: ‘pathological bodily process’ that occurs after a medical intervention.
– Does not assume causality – ‘causal adverse event’ assumes causality
• >1,000 specific AE terms in OAE now, mapped to MedDRA terms
OAE for AE data analysisRef: Sarntivijai et al., 2012PLoS ONE
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IDO: Infectious Disease Ontology
• IDO: represent the entire infectious disease domain
• Interoperability with other disease and health domains
• IDO-core: by Lindsay Cowell, Barry Smith, and others
Courtesy: figure kindly provided by Lindsay Cowell
IDO-core Central Terms:
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IDO Core-Extension Development Strategy
• IDO extensions are developed by extending IDO-core
OGMS
OBIGO BP
CL
I IDO-Core
IDO-Bac
IDO-Virus
IDO-Sa
IDO-Flu IDO-Mal
IDO-Par
IDO-Fun
IDO-Flav
IDO-TB
IDO-Sch
IDO-Asp
IDO-Cry
Courtesy: figure kindly provided by Lindsay Cowell
• We developed an IDO extension: Brucellosis Ontology
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IDOBRU: Brucellosis Ontology as an IDO Extension
• Focuses on the domain of zoonotic brucellosis, caused by Gram-negative bacterium Brucella.
• Incorporates all IDO-core terms, has over 880 Brucella-specific terms, and imports terms from other ontologies.
Citation: “Asiyah” Yu Lin, Zuoshuang Xiang, Yongqun He. Brucellosis Ontology (IDOBRU) as an extension of the Infectious Disease Ontology. Journal of Biomedical Semantics. 2011 Oct 31;2(1):9. PMID: 22041276.
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IDO-core is the top ontology of IDOBRU
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Vaccine Ontology (VO)
• VO: A biomedical ontology in the domain of vaccine and vaccination
• Support data integration, literature mining, and reasoning
• Integrated with VIOLIN• VIOLIN: a vaccine database and analysis
system, including many programs, e.g.:o ~3000 vaccineso Protegen: protective antigens. ~600o Vaxjo: vaccine adjuvants: > 100o Vaxign: vaccine designo Widely used by vaccine community
• Funded by a NIAID R01 grant
http://www.violinet.org/vaccineontology
http://www.violinet.org
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Many Ontology Tools developed during VO development
is_aontology
development tool
Hegroup RDF triple
store
Ontorat: generate new ontology
terms
OntoFox: reuse existing ontology
terms
is_a
Ontodog: generate ontology community
view
Ontobee: linked ontology
data server
uses
is_a
ontology application
tool
uses
uses
uses is_a
is_a
uses is_a
OntoCOG: COG enrichment
analysis tool
Ontobat: biodata analysis tool
(In development)
Ontology fetching tool Linked ontology data server
Mass generation of new terms
Ontology community view generator
Ontology data analysis
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VO Statistics and Development
# Class ObjectProperty Subtotal
VO 4800 7 4807BFO 2 22 38 60
RO 0 4 4CARO 9 0 9CHEBI 20 0 20DOID 57 0 57
GO 19 0 19OBI 36 11 47
OGMS 1 0 1PATO 17 0 17FMA 2 0 2IAO 18 2 20IDO 2 0 2
NCBITaxon 397 0 397PRO 2 0 2
UBERON 8 0 8UO 1 0 1
Subtotal 5411 62 5473
• OntoFox to import external terms and axioms from other 16 ontologies
• Ontorat to generate a large number of terms and axioms automatically
• VO includes >1000 vaccines for >20 host spp. against various diseases
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VO imports OBI terms for vaccine investigation
OBI/VO modeling of “vaccine protection
assay”
Reference: Brinkman et al. (2007). Modeling biomedical experimental processes with OBI. Journal of Biomedical Semantics. 2010, 1(Suppl 1):S7. PMID: 20626927.
OBI: Ontology for Biomedical Investigations
~20 communities involved
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Example: Afluria Influenza Vaccine
Afluria-1Flu vaccine
is_a
CSL Limited
intramuscular vaccination
adaptive immune response
is_manufactured
_byinactivated
chicken egg protein allergen
has_quality has_part
bearer_of
vaccine allergen
disposition
bearer_of
dose specification
viral vaccine-induced
immunization
has_specified_output_ofis_specified_
input_of
has_part bearer_of some ‘acquired immunity to Influenza virus’
age
viral pathogen target role
Influenza virus
has_participant
is_about
Bob (a human)
realizes
vaccine host role
has_quality
age measurement datum (value: 6
unit: month)
quality_is_measured_as
has_participant
realizes
bearer_of
measurementdata
is_a has_participant
plan specification
is_realized
-byhas_part
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U of Michigan Ontology Research
• UM Ontology Working Group:o Members: Marcy Harris, Alla Karnovsky, Frank Manion,
Oliver He, Asiyah Yu Lin, Jeff Cowall, … o Activities: Biweekly meetings, …o Developing a Clinical and Translational Research Ontology.
• UM MCubed pilot award:o Title: Ontology Development and Applications for Clinical
and Translational Scienceo To: Alla, Marcy, and Oliver; Period: 1.5 years
• UM CTSA: Michigan Institute for Clinical & Health Research (MICHR)o Ontology research needed to integrate huge datasets o Committed to collaborative community efforto One project: Informed Consent Ontology (ICO) (next slide)
• Case study: Head and neck cancer biorepository
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Informed Consent Ontology (ICO)• ICO: A prototype, aligned with BFO.• Currently focused on research permissions• UM CTSA Project Team:
Alla Karnovsky, Frank Manion, Marcy Harris, Oliver He, Nick Steneck, Blake Roessler
Reference: Development of an Informed Consent Ontology to Support Biobanking. Alla Karnovsky, Frank J. Manion, Oliver He, Terry Weymouth, V. Glenn Tarcea; Lisa Powell, Blake J. Roessler, Nicholas H. Steneck. AMIA 2012 Annual Symposium.
Protocol
Patient Record
Institutional Records
IRB/eResearch
Informed Consent Form
Subject matter expert view
Courtesy: figures kindly provided by Alla Karnovsky and Nickolas Steneck
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Clinical Data Integration Required• Records of millions of patients in UM Health System (UMHS)• Ontology is needed for true clinical data integration
Courtesy: figure kindly provided by Jeff Cowall
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Acknowledgements
Funding: NIH grants R01AI081062 & U54-DA-021519UM MCubed pilot project, MICHR (UM CTSA)
Oliver He Group:
• Zuoshuang “Allen” Xiang• “Asiyah” Yu Lin• Sirarat Sarntivijai
UM Literature Mining Collaborators:
• Arzucan Özgür • Junguk Hur
VO Collaborators:
Barry, Lindsay, Alan, Bjoern, ….
Barry Smith (BFO, OGMS, IDO, VO, ...)
OBI Consortium:
• Bjoern Peters• Jie Zheng• Chris Stoeckert• Alan Rutternberg• Melanie Courtot, …
UM Ontology Working Group Listed in a previous slide
Lindsay Cowell (IDO)
OGMS Development Team
• Albert Goldfain • Richard Scheuermann, …