PhenoGO: A Resource for Mining Clinical and Biological Data
Author Information
Author(s): Sam Lee, Eneida A Mendonça, Jianrong Li, Judith Blake, Carol Friedman, Yves A Lussier
Primary Institution: Center for Biomedical Informatics, Department of Medicine, The University of Chicago
Hypothesis
Can the PhenoGO database provide a comprehensive resource for gene-disease specific annotations across multiple species?
Conclusion
The PhenoGO resource significantly enhances existing Gene Ontology annotations by providing phenotypic context, achieving high accuracy in its evaluations.
Supporting Evidence
- The PhenoGO database now includes over 600,000 phenotypic contexts spanning eleven species.
- Precision of the mappings was found to be 85% and recall at 76% based on a comprehensive evaluation.
- The database was expanded to include annotations for ten additional species.
Takeaway
PhenoGO is like a big library that helps scientists understand how genes relate to diseases by organizing lots of information about different living things.
Methodology
The study used natural language processing and computational ontology methods to derive gene-disease associations and expand the PhenoGO database.
Limitations
The current version does not allow queries over specific taxa or experimental evidence codes in Gene Ontology.
Statistical Information
Confidence Interval
95% CI: 82%–89%
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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