Format

Send to

Choose Destination
See comment in PubMed Commons below
Expert Rev Vaccines. 2014 Jul;13(7):825-41. doi: 10.1586/14760584.2014.923762. Epub 2014 Jun 7.

Ontology-supported research on vaccine efficacy, safety and integrative biological networks.

Author information

  • 1Unit for Laboratory Animal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109, USA.

Abstract

While vaccine efficacy and safety research has dramatically progressed with the methods of in silico prediction and data mining, many challenges still exist. A formal ontology is a human- and computer-interpretable set of terms and relations that represent entities in a specific domain and how these terms relate to each other. Several community-based ontologies (including Vaccine Ontology, Ontology of Adverse Events and Ontology of Vaccine Adverse Events) have been developed to support vaccine and adverse event representation, classification, data integration, literature mining of host-vaccine interaction networks, and analysis of vaccine adverse events. The author further proposes minimal vaccine information standards and their ontology representations, ontology-based linked open vaccine data and meta-analysis, an integrative One Network ('OneNet') Theory of Life, and ontology-based approaches to study and apply the OneNet theory. In the Big Data era, these proposed strategies provide a novel framework for advanced data integration and analysis of fundamental biological networks including vaccine immune mechanisms.

KEYWORDS:

adverse event; data mining; interaction network; literature mining; meta-analysis; ontology; theory; vaccine; vaccine efficacy; vaccine safety

PMID:
24909153
PMCID:
PMC4815432
DOI:
10.1586/14760584.2014.923762
[PubMed - indexed for MEDLINE]
Free PMC Article
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Taylor & Francis Icon for PubMed Central
    Loading ...
    Support Center