Improving Brucella Vaccine Literature Indexing with Vaccine Ontology
Author Information
Author(s): Hur Junguk, Xiang Zuoshuang, Feldman Eva L, He Yongqun
Primary Institution: University of Michigan
Hypothesis
Application of Vaccine Ontology in SciMiner will aid vaccine literature indexing and mining of vaccine-gene interaction networks.
Conclusion
VO-SciMiner can be used to improve the efficiency for PubMed searching in the vaccine domain.
Supporting Evidence
- VO-SciMiner demonstrated high recall (91%) and precision (99%) from testing a separate set of 100 manually selected biomedical articles.
- VO-SciMiner indexing exhibited superior performance in retrieving Brucella vaccine-related papers over MeSH-based PubMed literature search.
- Using the abstracts of 14,947 Brucella-related papers, VO-SciMiner identified 140 Brucella genes associated with Brucella vaccines.
Takeaway
This study shows that using a special vocabulary for vaccines helps find more research papers about Brucella vaccines, making it easier for scientists to learn about them.
Methodology
Developed VO-SciMiner to index Brucella vaccine terms and analyze interactions between vaccines and genes using literature mining.
Limitations
The text mining approach may include false positives and does not guarantee functional associations between co-cited genes and vaccines.
Statistical Information
P-Value
p<0.05
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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