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DRASTIC--INSIGHTS: querying information in a plant gene expression database.
Davina K Button1, Kevan M A Gartland, Leslie D Ball
1Abertay Centre for the Environment, University of Abertay Dundee, Dundee DD1 1HG, Scotland, UK. davina.button@abertay.ac.uk
Nucleic Acids Research
|December 31, 2005
Summary
The DRASTIC database resource aids plant biology by cataloging gene expression changes. It helps identify plant genes responding to various environmental stresses and pathogens for systems biology research.
Area of Science:
- Plant biology
- Systems biology
- Molecular biology
Background:
- Signal transduction pathways are crucial for plant responses to environmental stimuli.
- Understanding gene regulation under stress is vital for crop improvement and agricultural resilience.
- Existing data on plant gene expression is fragmented across numerous publications.
Purpose of the Study:
- To create a centralized, data-driven resource for plant signal transduction pathways.
- To facilitate the identification of plant genes regulated by various treatments.
- To support systems biology investigations through intelligent data mining.
Main Methods:
- Development of a relational database (DRASTIC) integrating plant expressed sequence tags and gene expression data.
- Inclusion of over 17,700 records from 512 publications covering 73 plant species.
- Utilizing the INSIGHTS suite of web-based tools for data mining and pathway visualization.
Main Results:
- DRASTIC contains data on genes up- or down-regulated by pathogens, chemical exposure, drought, salt, and low temperature.
- The database enables rapid identification of genes responding to single or multiple treatments.
- Arabidopsis thaliana data is extensively represented, providing a model for plant research.
Conclusions:
- DRASTIC serves as a foundational resource for constructing and analyzing plant signal transduction pathways.
- The INSIGHTS tools facilitate hypothesis generation and understanding of gene expression patterns.
- This resource advances plant signaling research and systems biology approaches.