Skip to main content
Springer Nature Link
Log in

Development and Applications of Interoperable Biomedical Ontologies for Integrative Data and Knowledge Representation and Multiscale Modeling in Systems Medicine

  • Protocol
  • First Online:
Systems Medicine

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2486))

  • 1427 Accesses

Abstract

The data FAIR Guiding Principles state that all data should be Findable, Accessible, Interoperable, and Reusable. Ontology is critical to data integration, sharing, and analysis. Given thousands of ontologies have been developed in the era of artificial intelligence, it is critical to have interoperable ontologies to support standardized data and knowledge presentation and reasoning. For interoperable ontology development, the eXtensible ontology development (XOD) strategy offers four principles including ontology term reuse, semantic alignment, ontology design pattern usage, and community extensibility. Many software programs are available to help implement these principles. As a demonstration, the XOD strategy is applied to developing the interoperable Coronavirus Infectious Disease Ontology (CIDO). Various applications of interoperable ontologies, such as COVID-19 and kidney precision medicine research, are also introduced in this chapter.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Wilkinson MD, Dumontier M, Aalbersberg IJ et al (2016) The FAIR guiding principles for scientific data management and stewardship. Sci Data 3:160018. https://doi.org/10.1038/sdata.2016.18

    Article  PubMed  PubMed Central  Google Scholar 

  2. Hoehndorf R, Schofield PN, Gkoutos GV (2015) The role of ontologies in biological and biomedical research: a functional perspective. Brief Bioinform 16(6):1069–1080. https://doi.org/10.1093/bib/bbv011

    Article  PubMed  PubMed Central  Google Scholar 

  3. Bodenreider O (2008) Biomedical ontologies in action: role in knowledge management, data integration and decision support. Yearb Med Inform:67–79

    Google Scholar 

  4. Schulz S, Balkanyi L, Cornet R et al (2013) From concept representations to ontologies: a paradigm shift in health informatics? Healthc Inform Res 19(4):235–242. https://doi.org/10.4258/hir.2013.19.4.235

    Article  PubMed  PubMed Central  Google Scholar 

  5. Gonzalez-Beltran A, Maguire E, Sansone SA et al (2014) linkedISA: semantic representation of ISA-Tab experimental metadata. BMC Bioinformatics 15(Suppl 14):S4. https://doi.org/10.1186/1471-2105-15-S14-S4

    Article  PubMed  PubMed Central  Google Scholar 

  6. Malladi VS, Erickson DT, Podduturi NR et al (2015) Ontology application and use at the ENCODE DCC. Database (Oxford) 2015:bav010. https://doi.org/10.1093/database/bav010

    Article  CAS  Google Scholar 

  7. Dugan VG, Emrich SJ, Giraldo-Calderon GI et al (2014) Standardized metadata for human pathogen/vector genomic sequences. PLoS One 9(6):e99979. https://doi.org/10.1371/journal.pone.0099979

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Stodden V, Guo P, Ma Z (2013) Toward reproducible computational research: an empirical analysis of data and code policy adoption by journals. PLoS One 8(6):e67111. https://doi.org/10.1371/journal.pone.0067111

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Ashburner M, Ball CA, Blake JA et al (2000) Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25(1):25–29. https://doi.org/10.1038/75556

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Bandrowski A, Brinkman R, Brochhausen M et al (2016) The ontology for biomedical investigations. PLoS One 11(4):e0154556. https://doi.org/10.1371/journal.pone.0154556

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Brinkman RR, Courtot M, Derom D et al (2010) Modeling biomedical experimental processes with OBI. J Biomed Semantics 1(Suppl 1):S7. https://doi.org/10.1186/2041-1480-1-S1-S7

    Article  PubMed  PubMed Central  Google Scholar 

  12. Whetzel PL, Noy NF, Shah NH et al (2011) BioPortal: enhanced functionality via new Web services from the National Center for Biomedical Ontology to access and use ontologies in software applications. Nucleic Acids Res 39(Web Server issue):W541–W545. https://doi.org/10.1093/nar/gkr469

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Ong E, Xiang Z, Zhao B et al (2017) Ontobee: a linked ontology data server to support ontology term dereferencing, linkage, query and integration. Nucleic Acids Res 45(D1):D347–D352. https://doi.org/10.1093/nar/gkw918

    Article  CAS  PubMed  Google Scholar 

  14. Cote RG, Jones P, Martens L et al (2008) The Ontology Lookup Service: more data and better tools for controlled vocabulary queries. Nucleic Acids Res 36(Web Server issue):W372–W376. https://doi.org/10.1093/nar/gkn252

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Hoehndorf R, Slater L, Schofield PN et al (2015) Aber-OWL: a framework for ontology-based data access in biology. BMC Bioinformatics 16:26. https://doi.org/10.1186/s12859-015-0456-9

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Smith B, Ashburner M, Rosse C et al (2007) The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol 25(11):1251–1255. https://doi.org/10.1038/nbt1346

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. He Y, Xiang Z, Zheng J et al (2018) The eXtensible Ontology Development (XOD) principles and tool implementation to support ontology interoperability. J Biomed Semantics 9(1):3. https://doi.org/10.1186/s13326-017-0169-2

    Article  PubMed  PubMed Central  Google Scholar 

  18. Xiang Z, Zheng J, Lin Y et al (2015) Ontorat: automatic generation of new ontology terms, annotations, and axioms based on ontology design patterns. J Biomed Semantics 6(1):4. https://doi.org/10.1186/2041-1480-6-4

    Article  PubMed  PubMed Central  Google Scholar 

  19. Xiang Z, Courtot M, Brinkman RR et al (2010) OntoFox: web-based support for ontology reuse. BMC Res Notes 3:175. https://doi.org/10.1186/1756-0500-3-175. 1756-0500-3-175 [pii]

    Article  PubMed  PubMed Central  Google Scholar 

  20. Zheng J, Xiang Z, Stoeckert CJ Jr et al (2014) Ontodog: a web-based ontology community view generation tool. Bioinformatics 30(9):1340–1342. https://doi.org/10.1093/bioinformatics/btu008

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Jackson RC, Balhoff JP, Douglass E et al (2019) ROBOT: a tool for automating ontology workflows. BMC Bioinformatics 20(1):407. https://doi.org/10.1186/s12859-019-3002-3

    Article  PubMed  PubMed Central  Google Scholar 

  22. Overton JA, Dietze H, Essaid S et al (2015) ROBOT: a command-line tool for ontology development. In: Proceedings of the 2015 international conference on biomedical ontologies (ICBO), Lisbon, Portugal, July 27-30, 2015, vol 1515, pp 1–2. http://ceur-ws.org/Vol-1515/demo1516.pdf

  23. He Y, Yu H, Ong E et al (2020) CIDO, a community-based ontology for coronavirus disease knowledge and data integration, sharing, and analysis. Sci Data 7(1):181. https://doi.org/10.1038/s41597-020-0523-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. NCBITaxon: an ontology representation of the NCBI organismal taxonomy. http://obofoundry.org/ontology/ncbitaxon.html

  25. Babcock S, Cowell LG, Smith B (2020) The infectious disease ontology in 2020. BioRxiv: submitted on April 12, 2020. BIORXIV/2020/038224

    Google Scholar 

  26. Kibbe WA, Arze C, Felix V et al (2015) Disease ontology 2015 update: an expanded and updated database of human diseases for linking biomedical knowledge through disease data. Nucleic Acids Research 43(Database issue):D1071–D1078. https://doi.org/10.1093/nar/gku1011

    Article  CAS  PubMed  Google Scholar 

  27. Groza T, Kohler S, Moldenhauer D et al (2015) The human phenotype ontology: semantic unification of common and rare disease. Am J Hum Genet 97(1):111–124. https://doi.org/10.1016/j.ajhg.2015.05.020

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. PATO—phenotypic quality ontology. https://github.com/pato-ontology/pato/

  29. Mungall CJ, Torniai C, Gkoutos GV et al (2012) Uberon, an integrative multi-species anatomy ontology. Genome Biol 13(1):R5. https://doi.org/10.1186/gb-2012-13-1-r5

    Article  PubMed  PubMed Central  Google Scholar 

  30. Diehl AD, Meehan TF, Bradford YM et al (2016) The cell ontology 2016: enhanced content, modularization, and ontology interoperability. J Biomed Semantics 7(1):44. https://doi.org/10.1186/s13326-016-0088-7

    Article  PubMed  PubMed Central  Google Scholar 

  31. Natale DA, Arighi CN, Blake JA et al (2014) Protein ontology: a controlled structured network of protein entities. Nucleic Acids Res 42(Database issue):D415–D421. https://doi.org/10.1093/nar/gkt1173

    Article  CAS  PubMed  Google Scholar 

  32. He Y (2013) Announcement of the Ontology of Genes and Genomes (OGG). https://groups.google.com/forum/#!topic/ogg-discuss/wy0132CCdNA

  33. Hastings J, Owen G, Dekker A et al (2016) ChEBI in 2016: improved services and an expanding collection of metabolites. Nucleic Acids Res 44(D1):D1214–D1219. https://doi.org/10.1093/nar/gkv1031

    Article  CAS  PubMed  Google Scholar 

  34. Musen MA (2015) The Protégé project: a look back and a look forward. AI Matter 1(4):4–12. https://doi.org/10.1145/2557001.25757003

    Article  Google Scholar 

  35. Horridge M, Tudorache T, Nuylas C et al (2014) WebProtege: a collaborative web-based platform for editing biomedical ontologies. Bioinformatics 30(16):2384–2385. https://doi.org/10.1093/bioinformatics/btu256

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Ong E, He Y (2016) Community-based ontology development, annotation and discussion with MediaWiki extension Ontokiwi and Ontokiwi-based Ontobedia. In: AMIA joint summits on translational science proceedings, 2016, pp 65–74

    Google Scholar 

  37. Liu Y, Chan W, Wang Z et al. (2020) Ontological and bioinformatic analysis of anti-coronavirus drugs and their implication for drug repurposing against COVID-19. Preprints:2020030413. https://doi.org/10.20944/preprints202003.0413.v1

  38. He Y, Sarntivijai S, Lin Y et al (2014) OAE: the ontology of adverse events. J Biomed Semantics 5:29. https://doi.org/10.1186/2041-1480-5-29

    Article  PubMed  PubMed Central  Google Scholar 

  39. Sarntivijai S, Lin Y, Xiang Z et al (2014) CLO: the cell line ontology. J Biomed Semantics 5:37. https://doi.org/10.1186/2041-1480-5-37

    Article  PubMed  PubMed Central  Google Scholar 

  40. He Y, Wang H, Zheng J et al (2019) OHMI: the ontology of host-microbiome interactions. J Biomed Semantics 10(1):25. https://doi.org/10.1186/s13326-019-0217-1

    Article  PubMed  PubMed Central  Google Scholar 

  41. He Y, Steck B, Ong E et al (2018) KTAO: a kidney tissue atlas ontology to support community-based kidney knowledge base development and data integration. In: International conference on biomedical ontology 2018 (ICBO-2018), Corvallis, Oregon, USA, August 7–10, 2018, pp 1–6

    Google Scholar 

  42. He Y, Ong E, Schaub J et al (2019) OPMI: the ontology of precision medicine and investigation and its support for clinical data and metadata representation and analysis. In: The 10th international conference on biomedical ontology (ICBO-2019), July 30–August 2, Buffalo, NY, USA, 2019, pp 1–10

    Google Scholar 

  43. Ong E, Wang LL, Schaub J et al (2020) Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project. Nat Rev Nephrol 16(11):686–696. https://doi.org/10.1038/s41581-020-00335-w

    Article  PubMed  PubMed Central  Google Scholar 

  44. Huffman A, Masci AM, Zheng J, Sanati N, Brunson T, Wu G, He Y. CIDO ontology updates and secondary analysis of host responses to COVID-19 infection based on ImmPort reports and literature. J Biomed Semant 12, 18 (2021). https://doi.org/10.1186/s13326-021-00250-4. PMID:34454610. PMCID: PMC8400831.

Download references

Acknowledgments

This work was supported by NIH-NIAID grants 1R01AI081062 and 1UH2AI13293. Dr. Junguk Hur’s review and editing are appreciated.

Author information

Authors and Affiliations

  1. Unit for Laboratory Animal Medicine, Department of Microbiology and Immunology, Center of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA

    Yongqun He

Authors
  1. Yongqun He
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yongqun He .

Editor information

Editors and Affiliations

  1. Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA

    Jane P.F. Bai

  2. School of Medicine and Health Sciences, University of North Dakota, Grand Forks, ND, USA

    Junguk Hur

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

He, Y. (2022). Development and Applications of Interoperable Biomedical Ontologies for Integrative Data and Knowledge Representation and Multiscale Modeling in Systems Medicine. In: Bai, J.P., Hur, J. (eds) Systems Medicine. Methods in Molecular Biology, vol 2486. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2265-0_12

Download citation

  • DOI: https://doi.org/10.1007/978-1-0716-2265-0_12

  • Published:

  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-2264-3

  • Online ISBN: 978-1-0716-2265-0

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics