abstract
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Although discovery-scale biomedical datasets represent valuable assets for hypothesis generation, model testing and data validation, the infrastructure supporting their re-use lacksorganization and consistency. Here, using relative abundance transcriptomic datasets in the field of nuclear receptor signaling as a proof-of-principle data type, we established a model for improving the discoverability, accessibility andcitability of published ‘omics datasets.