ESPERANTO: a GLP-field sEmi-SuPERvised toxicogenomics metadAta curatioN TOol.

ABSTRACT:

Summary

Biological data repositories are an invaluable source of publicly available research evidence. Unfortunately, the lack of convergence of the scientific community on a common metadata annotation strategy has resulted in large amounts of data with low FAIRness (Findable, Accessible, Interoperable and Reusable). The possibility of generating high-quality insights from their integration relies on data curation, which is typically an error-prone process while also being expensive in terms of time and human labour. Here, we present ESPERANTO, an innovative framework that enables a standardized semi-supervised harmonization and integration of toxicogenomics metadata and increases their FAIRness in a Good Laboratory Practice-compliant fashion. The harmonization across metadata is g

SUBMITTER: Di Lieto E 

PROVIDER: S-EPMC10313344 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature