ESPERANTO: a GLP-field sEmi-SuPERvised toxicogenomics metadAta curatioN TOol
Bioinformatics (Oxford, England)(2023)
摘要
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 guaranteed with the definition of an ad hoc vocabulary. The tool interface is designed to support the user in metadata harmonization in a user-friendly manner, regardless of the background and the type of expertise.Availability and implementationESPERANTO and its user manual are freely available for academic purposes at . The input and the results showcased in are available at the same link.
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关键词
toxicogenomics metadata curation tool,glp-field,semi-supervised
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