Skip to main content

Biomedical Data/Content Acquisition, Curation

  • Reference work entry
  • First Online:
Encyclopedia of Database Systems
  • 12 Accesses

Synonyms

Biomedical data annotation

Definition

The largest source of biomedical knowledge is the published literature, where results of experimental studies are reported in natural language. Published literature is hard to query, integrate computationally or to reason over. The task of reading published papers (or other forms of experimental results such as pharmacogenomics datasets) and distilling them down into structured knowledge that can be stored in databases as well as knowledgebases is called curation. The statements comprising the structured knowledge are called annotations. The level of structure in annotation statements can vary from loose declarations of “associations” between concepts (such as associating a paper with the concept “colon cancer”) to statements that declare a precisely defined relationship between concepts with explicit semantics. There is an inherent tradeoff between the level of detail of the structured annotations and the time and effort required to...

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 4,499.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 6,499.99
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

Recommended Reading

  1. Ashburner M et al. Geneontology: tool for the unification of biology. Nat Genet. 2000;25(1):25–9.

    Article  Google Scholar 

  2. Baral C et al. A knowledge based approach for representing and reasoning about signaling networks. Bioinformatics. 2004;20(1):15–22.

    Article  Google Scholar 

  3. Baumgartner Jr WA et al. Manual curation is not sufficient for annotation of genomic databases. Bioinformatics. 2007;23(13):41–8.

    Article  Google Scholar 

  4. BioPax-Consortium. BioPAX: biological pathways exchange, 2006. Available from: http://www.biopax.org/2006

  5. Bodenreider O, Stevens R. Bio-ontologies: current trends and future directions. Brief. Bioinform. 2006;7(3):256–74.

    Article  Google Scholar 

  6. Camon EB et al. An evaluation of GO annotation retrieval for BioCreAtIvE and GOA. BMC Bioinf. 2005;6(Suppl 1):S17.

    Article  Google Scholar 

  7. Cherry JM et al. SGD: saccharomyceas genome database. Nucl Acids Res. 1998;26(1):73–9.

    Article  Google Scholar 

  8. Ciccaresse P, Wu E, Clark T. An overview of the SWAN 1.0 ontology of scientific discourse. In: Proceeding of 16th International World Wide Web Conference; 2007.

    Google Scholar 

  9. Clark T, Kinoshita J. Alzforum and SWAN: the present and future of scientific web communities. Brief Bioinform. 2007;8(3):163–71.

    Article  Google Scholar 

  10. Gao Y et al. SWAN: a distributed knowledge infrastructure for Alzheimer disease research. J Web Semant. 2006;4(3):222–8.

    Article  MathSciNet  Google Scholar 

  11. Gibson M. Phenote. Berkeley Bioinformatics and Ontology Project (BBOP), National Center for Biomedical Ontology, Lawrence Berkeley National Laboratory; 2007.

    Google Scholar 

  12. Hunter L, Cohen KB. Biomedical language processing: what’s beyond PubMed? Mol Cell. 2006;21(5):589–94.

    Article  Google Scholar 

  13. Joshi-Tope G et al. Reactome: a knowledge base of biological pathways. Nucl Acids Res. 2005;33(Database Issue):D428–32.

    Article  Google Scholar 

  14. Karp PD. An ontology for biological function based on molecular interactions. Bioinformatics. 2000;16(3):269–85.

    Article  Google Scholar 

  15. Karp PD. Pathway databases: a case study in computational symbolic theories. Science. 2001;293(5537):2040–4.

    Article  Google Scholar 

  16. Katz AE et al. Molecular staging of genitourinary malignancies. Urology. 1996;47(6):948–58.

    Article  Google Scholar 

  17. Leslie M. Netwatch. Science. 2006;312(5781):1721.

    Google Scholar 

  18. Massar JP et al. BioLingua: a programmable knowledge environment for biologists. Bioinformatics. 2004;21(2):199–207.

    Article  Google Scholar 

  19. Racunas SA et al. HyBrow: a prototype system for computer-aided hypothesis evaluation. Bioinformatics. 2004;20(Suppl 1):257–64.

    Article  Google Scholar 

  20. Reactome Curator Guide. http://wiki.reactome.org/index.php/Reactome_Curator_Guide

  21. Rise of the Bio-Librarian - the field of biocuration expands as the data grow. http://www.the-scientist.com/article/display/23316/

  22. Ruttenberg A et al. Advancing translational research with the Semantic Web. BMC Bioinf. 2007;8(Suppl 3):S2.

    Article  Google Scholar 

  23. Rzhetsky A et al. GeneWays: a system for extracting, analyzing, visualizing, and integrating molecular pathway data. J Biomed Inform. 2004;37(1):43–53.

    Article  Google Scholar 

  24. Second International Biocuration Meeting, San Jose, 25–28 Oct, 2007. http://biocurator.org/Mtg2007/index.html

  25. Shrager J et al. Deductive biocomputing. PLoS One. 2007;2(4):e339.

    Article  Google Scholar 

  26. Sim I, Olasov B, Carini S. The Trial Bank system: capturing randomized trials for evidence-based medicine. In: American Medical Informatics Association Annual Symposium Proceedings; 2003. p. 1076

    Google Scholar 

  27. Smith B et al. Relations in biomedical ontologies. Genome Biol. 2005;6(5):R46.

    Article  Google Scholar 

  28. Spasic I, Ananiadou S, McNaught J, Kumar A. Text mining and ontologies in biomedicine: making sense of raw text. Brief Bioinform. 2005;6(3):239–51.

    Article  Google Scholar 

  29. Tari L., et al. BioQA. 2007. http://cbioc.eas.asu.edu/bioQA/v2/index.html

  30. The National Center for Biomedical Ontology. 2006. Available at: www.biontology.org

    Google Scholar 

  31. Thorn CF, Klein TE, Altman RB. PharmGKB: the pharmacogenetics and pharmacogenomics knowledge base. In: Methods in molecular biology, vol. 311. Springer. p. 179–91.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nigam Shah .

Editor information

Editors and Affiliations

Section Editor information

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Science+Business Media, LLC, part of Springer Nature

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Shah, N. (2018). Biomedical Data/Content Acquisition, Curation . In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_37

Download citation

Publish with us

Policies and ethics