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The amount of omics data in the public domain is increasing every year. Modern science has become a data-intensive discipline. Innovative solutions for data management, data sharing, and for discovering novel datasets are therefore increasingly required. In 2016, we released the first version of the Omics Discovery Index (OmicsDI) as a light-weight system to aggregate datasets across multiple public omics data resources. OmicsDI aggregates genomics, transcriptomics, proteomics, metabolomics and multiomics datasets, as well as computational models of biological processes. Here, we propose a set of novel metrics to quantify the attention and impact of biomedical datasets. A complete framework (now integrated into OmicsDI) has been implemented in order to provide and evaluate those metrics. Finally, we propose a set of recommendations for authors, journals and data resources to promote an optimal quantification of the impact of datasets.
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Yasset Pérez‐Riverol
European Bioinformatics Institute
Andrey Zorin
European Bioinformatics Institute
Gaurhari Dass
European Bioinformatics Institute
Nature Communications
SHILAP Revista de lepidopterología
University of California, Los Angeles
European Bioinformatics Institute
Beijing Proteome Research Center
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Pérez‐Riverol et al. (Mon,) studied this question.
synapsesocial.com/papers/69d776ffb843b2be9948fe1b — DOI: https://doi.org/10.1038/s41467-019-11461-w
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