Background: Recent years have seen an explosion in plant genomics, as the difficulties inherent in sequencing and functionally analyzing these biologically and economically significant organisms have been overcome. Arabidopsis thaliana, a versatile model organism, represents an opportunity to evaluate the predictive power of biological network inference for plant functional genomics.Results: Here, we provide a compendium of functional relationship networks for Arabidopsis thaliana leveraging data integration based on over 60 microarray, physical and genetic interaction, and literature curation datasets. These include tissue, biological process, and development stage specific networks, each predicting relationships specific to an individual biological context. These biological networks enable the rapid investigation of uncharacterized genes in specific tissues and developmental stages of interest and summarize a very large collection of A. thaliana data for biological examination. We found validation in the literature for many of our predicted networks, including those involved in disease resistance, root hair patterning, and auxin homeostasis.Conclusions: These context-specific networks demonstrate that highly specific biological hypotheses can be generated for a diversity of individual processes, developmental stages, and plant tissues in A. thaliana. All predicted functional networks are available online at http://function.princeton.edu/arathGraphle.
All Science Journal Classification (ASJC) codes
- Applied Mathematics
- Molecular Biology
- Structural Biology
- Computer Science Applications
- Modeling and Simulation