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Infectious Disease Ontology

  • Lindsay Grey Cowell
  • Barry Smith
Chapter

Abstract

In the last decade, technological developments have resulted in tremendous increases in the volume and diversity of the data and information that must be processed in the course of biomedical and clinical research and practice. Researchers are at the same time under ever greater pressure to share data and to take steps to ensure that data resources are interoperable. The use of ontologies to annotate data has proven successful in supporting these goals and in providing new possibilities for the automated processing of data and information. More recently, ontologies have been shown to have significant benefits both for the analysis of data resulting from high-throughput technologies and for automated reasoning applications, and this has led to organized attempts to improve the structure and formal rigor of ontologies in ways that will better support computational analysis and reasoning. In this chapter, we describe different types of vocabulary resources and emphasize those features of formal ontologies that make them most useful for computational applications. We describe current uses of ontologies and discuss future goals for ontology-based computing, focusing on its use in the field of infectious diseases. We review the largest and most widely used vocabulary resources relevant to the study of infectious diseases and conclude with a description of the Infectious Disease Ontology (IDO) suite of interoperable ontology modules that together cover the entire infectious disease domain.

Keywords

Gene Ontology Clinical Decision Support System Automate Reasoning Translational Medicine Ontology Development 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

LGC’s contributions were supported by a Career Award from the Burroughs-Wellcome Fund and NIAID grants R01 AI077706 and R01 AI068804. BS’s contributions were funded in part through the NIH Roadmap for Medical Research grant to the National Center for Biomedical Ontology (1 U 54 HG004028). Initial development of the Infectious Disease Ontology as well as the Infectious Disease Ontology meetings were generously supported by the Burroughs-Wellcome Fund.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Lindsay Grey Cowell
    • 1
  • Barry Smith
    • 1
  1. 1.Department of Biostatistics and BioinformaticsDuke University Medical CenterDurhamUSA

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