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Quantifying the impact of public omics data

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...

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Autores principales: Perez-Riverol, Yasset, Zorin, Andrey, Dass, Gaurhari, Vu, Manh-Tu, Xu, Pan, Glont, Mihai, Vizcaíno, Juan Antonio, Jarnuczak, Andrew F., Petryszak, Robert, Ping, Peipei, Hermjakob, Henning
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6683138/
https://www.ncbi.nlm.nih.gov/pubmed/31383865
http://dx.doi.org/10.1038/s41467-019-11461-w
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author Perez-Riverol, Yasset
Zorin, Andrey
Dass, Gaurhari
Vu, Manh-Tu
Xu, Pan
Glont, Mihai
Vizcaíno, Juan Antonio
Jarnuczak, Andrew F.
Petryszak, Robert
Ping, Peipei
Hermjakob, Henning
author_facet Perez-Riverol, Yasset
Zorin, Andrey
Dass, Gaurhari
Vu, Manh-Tu
Xu, Pan
Glont, Mihai
Vizcaíno, Juan Antonio
Jarnuczak, Andrew F.
Petryszak, Robert
Ping, Peipei
Hermjakob, Henning
author_sort Perez-Riverol, Yasset
collection PubMed
description 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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spelling pubmed-66831382019-08-07 Quantifying the impact of public omics data Perez-Riverol, Yasset Zorin, Andrey Dass, Gaurhari Vu, Manh-Tu Xu, Pan Glont, Mihai Vizcaíno, Juan Antonio Jarnuczak, Andrew F. Petryszak, Robert Ping, Peipei Hermjakob, Henning Nat Commun Article 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. Nature Publishing Group UK 2019-08-05 /pmc/articles/PMC6683138/ /pubmed/31383865 http://dx.doi.org/10.1038/s41467-019-11461-w Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Perez-Riverol, Yasset
Zorin, Andrey
Dass, Gaurhari
Vu, Manh-Tu
Xu, Pan
Glont, Mihai
Vizcaíno, Juan Antonio
Jarnuczak, Andrew F.
Petryszak, Robert
Ping, Peipei
Hermjakob, Henning
Quantifying the impact of public omics data
title Quantifying the impact of public omics data
title_full Quantifying the impact of public omics data
title_fullStr Quantifying the impact of public omics data
title_full_unstemmed Quantifying the impact of public omics data
title_short Quantifying the impact of public omics data
title_sort quantifying the impact of public omics data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6683138/
https://www.ncbi.nlm.nih.gov/pubmed/31383865
http://dx.doi.org/10.1038/s41467-019-11461-w
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