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Disease Ontology: mechanistic profiles of human disease



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Disease Ontology: mechanistic profiles of human disease

  1. 1. The Human Disease Ontology Project mechanistic profiles of human disease for biomedical and clinical research Funding: NIH/NHGRI Genomic Resource U41 HG008735-01A1 Lynn M. Schriml, Ph.D. University of Maryland School of Medicine Institute for Genome Science
  2. 2. axis of classification 2003 (ICD, MESH, NCI)  Semantic Relationships, DAG Persistent Identifiers: DOIDs DO R01 – DO Classification Website OBO Foundry domain ontology 2008 2017 10,598 disease terms ++ ~ 1000 new terms/yr Term expansion Outreach Genetic Diseases NHGRI U41 Genomic Resource CCBY → CC0 open license 2020 DO Website (in 2020) Users: up 15.8 %, 30,207, 142 countries DO xRefs GARD:1921; MESH:3466; OMIM:4649; ICD9CM:2117; ICD10CM:3520; NCI:4397; Orphanet:1845 12,242 cited definition sources (PubMed IDs, databases)
  3. 3. Axioms Alzheimer’s disease Parkinson’s Disease pediatric cancers acute lymphoblastic leukemia B-lymphoblastic leukemia/lymphoma hypersensitivity diseases genetic diseases: polygenic, digenic physical disorders Syndromes asthma diabetes Term mappings DO Releas es DO Slims databases tools (27) ontologies DO reports Disease re- classifications (QC & MESH, NCI, syndromes, synonyms) (15) DO slims DO_cancer_slim DO_AGR_slim DO citing papers (699) Linked data Imports OBO Foundry Ontologies Community Automated DO xref assessment Term requests (ontology enrichment) GitHub
  4. 4. Axiom s • Codify disease to disease relationships • Statements asserting SubClass • Views/Mechanisms of Disease
  5. 5. Axioms Disease to Disease Relatedness Statement
  6. 6. Wikidata SPARQL queries Drug-Drug interactions Drugs – disease – target gene - GO Linking biomedical data through disease Gene Wikidata semantic network linking genes, drugs and diseases with nodes and edges populated automatically by ‘bots’ that integrate data from trusted authorities such as NCBI’s Entrez Gene, PubChem, and the DO.  DO – NDF-RT – ChEMBL  Pathways: Reactome, Wikipathways
  7. 7. Clinical Team Carol Greene, Cynthia Bearer, Richard Lichenstein, Katherine Bisordi Medical Student Nicole Campion (Class of 2020) Connor Oates (Mount Sinai), David Kurland (NYU Langone Medical Center) Sue Bello, Melody Swen Becky Jackson Mike Schor Dustin Olley James Munro Carrie McCracken, Michelle Giglio IGS - IFX Team

Editor's Notes

  • Domain – Vocabs to Semantics – Devise Classifications (update) – Update Model – Automated Releases – New term requests – Community Resource -

    DO began – combining clinical vocabularies to create a ‘disease focused ontology’
    Rex Chisholm and Warren Kibbe – Northwestern
    DAG: Rooted Directed Acyclic Graph
    1000 terms added by our curation team each year, ~50% from term requests – track in our GitHub site
    Textual definitions - available for 75% of the DO’s 10,598 disease terms.
    Each definition is written by a DO curator, following specific definition design principles.

    Releases – one to two per month – ROBOT tool ( runs
    automatically with each GitHub commit, running a series of consistency and rigor checks – Run through Travis CI. Our build process runs further QC tests and produces a suite of reports for quality control assessment.

    Domain – all types of disease: common, Mendelian and complex and rare diseases – which we continue to curate and add to the DO
  • Schematic of DO’s World
    - lets begin at the center, now look to the left, paying attention to inward pointing arrows.

    Term Requests – Nicole
  • Defining mechanisms
  • GO Biological Process. - can extract Wikidata data
  • ×