RegenDbase—the Comparative Models of Regeneration Database—provides a systems-level view of genes across models of tissue regeneration to advance knowledge of regenerative biology and stem cell self-renewal.
RegenDbase facilitates new hypotheses about how genes regulate the regenerative response by integrating mRNA and microRNA expression data from diverse models of regeneration together with data from embryonic and induced pluripotent stem cells.
We integrate functional genomic datasets with up-to-date gene and genome annotations, Gene Ontology annotations, pathway annotations, gene orthologs, gene interactions, and a comprehensive set of miRNA target predictions for human, mouse, zebrafish, and nematode. We also provide consistent annotation of experiments and sample attributes to facilitate cross-experiment analyses.
RegenDbase is being developed by the MDI Biological Laboratory under its COBRE in Regenerative Biology and Medicine.
The RegenDbase Team appreciates its collaboration with Dr. Voot Yin and his laboratory, along with the Updike, Coffman, and Rieger laboratories at the MDI Biological Laboratory.
This project is funded by Institutional Development Award (IDeA) grants P20GM103423 and P20GM104318 from the National Institute of General Medical Sciences of the National Institutes of Health.
Finally, RegenDbase appreciates the many scientific resources from which it integrates data.