Quantifying the impact of public omics data View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-08-05

AUTHORS

Yasset Perez-Riverol, Andrey Zorin, Gaurhari Dass, Manh-Tu Vu, Pan Xu, Mihai Glont, Juan Antonio Vizcaíno, Andrew F. Jarnuczak, Robert Petryszak, Peipei Ping, Henning Hermjakob

ABSTRACT

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. More... »

PAGES

3512

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41467-019-11461-w

DOI

http://dx.doi.org/10.1038/s41467-019-11461-w

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1120129989

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/31383865


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