This project focuses on integrating comparative multi-omic data from model organisms with human regulatory landscapes to better understand tissue regeneration. The DC will compare multi-omic datasets generated by the DANIO-ReCODE network with established reference data from the DANIO-CODE consortium. By integrating these datasets with the targPred platform, the DC aims to enrich human regulatory landscapes with developmental and regenerative information from model organisms while linking newly identified regulatory elements to human disease and phenotype ontologies. This integration will add value to both resources: DANIO-ReCODE data will gain greater translational relevance through human disease associations, while targPred will be extended with developmental and regenerative regulatory information from model organisms. The DC will also develop interactive visualization tools to facilitate the exploration of these comparative multi-omic datasets. This work will generate prioritized biological hypotheses for experimental validation within the DANIO-ReCODE network, strengthening the translation of regulatory discoveries from model organisms to human biology.
