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Analysis of Protein Import into Chloroplasts Isolated from Stressed Plants
Published on: November 1, 2016
Enhancing data integration with text analysis to find proteins implicated in plant stress response
Keywan Hassani-Pak1, Roxane Legaie, Catherine Canevet
1Centre for Mathematical and Computational Biology, Rothamsted Research, Harpenden AL5 2JQ, UK.
Journal of Integrative Bioinformatics
|April 9, 2010
Summary
This study introduces text mining to the Ondex framework, enhancing gene prioritization for plant stress response research. It integrates bioinformatics data and scientific literature to uncover key protein-stress associations missed by traditional methods.
Area of Science:
- Genomics
- Bioinformatics
- Plant Biology
Background:
- High-throughput genomic studies generate numerous candidate genes requiring prioritization.
- Gene prioritization relies on evidence linking gene products to biological processes.
- Bioinformatics databases and scientific literature are key evidence sources.
Purpose of the Study:
- To extend the Ondex data integration framework with text mining capabilities.
- To consistently access evidence from both bioinformatics databases and the scientific literature.
- To identify key protein-stress associations in plant stress response.
Main Methods:
- Utilized text mining techniques on Medline abstracts.
- Integrated text mining with the Ondex data integration framework.
- Applied scoring metrics to identify protein-stress associations in Arabidopsis.
Main Results:
- Created a knowledge base of Arabidopsis proteins involved in plant stress response.
- Highlighted proteins using scientific literature that were not identified through data integration alone.
- Demonstrated the value of text mining for uncovering novel gene-disease associations.
Conclusions:
- Text mining features in Ondex enhance the identification of relevant genes from scientific literature.
- The integrated approach provides a more comprehensive view of gene function and biological relevance.
- Ondex offers an open-source solution for advanced data integration and text mining in biological research.
