1:00pm to 2:00pm |
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The Infectious Disease Ontology as a Foundation for the Integration, Analysis, and Interpretation of Infectious Disease Data
(Academic)
Virginia Bioinformatics Institute's CyberInfrastructure Group (CIG) Seminar Series
This will be the first seminar in the new CIG Seminar Series. The series will consist of about four seminars a year and feature researchers of note from the international scientific community speaking on a variety
of topics related to cyberinfrastructure.
Title: The Infectious Disease Ontology as a Foundation for the Integration, Analysis, and Interpretation of Infectious Disease Data
Speaker: Lindsay Cowell, Department of Biostatistics and
Bioinformatics, Duke University Medical Center
Abstract: In the last decade, technological developments have resulted in tremendous increases in the volumes of data and diversity of types of data that must be processed in the course of biomedical research, and this increase is certain to continue in the future. The result is an
urgent need for methods to increase the extent to which computers support data retrieval, integration, analysis, and interpretation. The use of ontologies (controlled, structured terminologies) to annotate data has proven successful in supporting automated data integration and
in facilitating human interpretation of data. More recently, ontologies have been shown to have benefits for the analysis of data resulting from high-throughput technologies and for automated reasoning applications,
including text and data mining. 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, and at the same time preserve biological accuracy.
In this talk, I will introduce ontology and describe how ontologies are currently being used in biomedical research. I will review available ontology resources with content relevant to the infectious disease domain, and describe the Infectious Disease Ontology (IDO) suite of ontology modules. The IDO ontologies are being developed to support the data integration and analysis needs of infectious disease researchers, providing a formal representation of relevant entities and the relationships between them, across three dimensions:
-- biological scale (e.g. protein, cell, organism, population),
-- organism role (e.g. host, pathogen, vector), and
-- pathogen type (e.g. Staphylococcus aureus, Plasmodium falciparum, HIV).
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