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Analysis of impact metrics for the Protein Data Bank
Since 1971, the Protein Data Bank (PDB) archive has served as the single, global repository for open access to atomic-level data for biological macromolecules. The archive currently holds >140,000 structures (>1 billion atoms). These structures are the molecules of life found in all organisms....
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6190746/ https://www.ncbi.nlm.nih.gov/pubmed/30325351 http://dx.doi.org/10.1038/sdata.2018.212 |
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author | Markosian, Christopher Di Costanzo, Luigi Sekharan, Monica Shao, Chenghua Burley, Stephen K. Zardecki, Christine |
author_facet | Markosian, Christopher Di Costanzo, Luigi Sekharan, Monica Shao, Chenghua Burley, Stephen K. Zardecki, Christine |
author_sort | Markosian, Christopher |
collection | PubMed |
description | Since 1971, the Protein Data Bank (PDB) archive has served as the single, global repository for open access to atomic-level data for biological macromolecules. The archive currently holds >140,000 structures (>1 billion atoms). These structures are the molecules of life found in all organisms. Knowing the 3D structure of a biological macromolecule is essential for understanding the molecule’s function, providing insights in health and disease, food and energy production, and other topics of concern to prosperity and sustainability. PDB data are freely and publicly available, without restrictions on usage. Through bibliometric and usage studies, we sought to determine the impact of the PDB across disciplines and demographics. Our analysis shows that even though research areas such as molecular biology and biochemistry account for the most usage, other fields are increasingly using PDB resources. PDB usage is seen across 150 disciplines in applied sciences, humanities, and social sciences. Data are also re-used and integrated with >400 resources. Our study identifies trends in PDB usage and documents its utility across research disciplines. |
format | Online Article Text |
id | pubmed-6190746 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-61907462018-10-29 Analysis of impact metrics for the Protein Data Bank Markosian, Christopher Di Costanzo, Luigi Sekharan, Monica Shao, Chenghua Burley, Stephen K. Zardecki, Christine Sci Data Analysis Since 1971, the Protein Data Bank (PDB) archive has served as the single, global repository for open access to atomic-level data for biological macromolecules. The archive currently holds >140,000 structures (>1 billion atoms). These structures are the molecules of life found in all organisms. Knowing the 3D structure of a biological macromolecule is essential for understanding the molecule’s function, providing insights in health and disease, food and energy production, and other topics of concern to prosperity and sustainability. PDB data are freely and publicly available, without restrictions on usage. Through bibliometric and usage studies, we sought to determine the impact of the PDB across disciplines and demographics. Our analysis shows that even though research areas such as molecular biology and biochemistry account for the most usage, other fields are increasingly using PDB resources. PDB usage is seen across 150 disciplines in applied sciences, humanities, and social sciences. Data are also re-used and integrated with >400 resources. Our study identifies trends in PDB usage and documents its utility across research disciplines. Nature Publishing Group 2018-10-16 /pmc/articles/PMC6190746/ /pubmed/30325351 http://dx.doi.org/10.1038/sdata.2018.212 Text en Copyright © 2018, The Author(s) http://creativecommons.org/licenses/by/4.0/ 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 | Analysis Markosian, Christopher Di Costanzo, Luigi Sekharan, Monica Shao, Chenghua Burley, Stephen K. Zardecki, Christine Analysis of impact metrics for the Protein Data Bank |
title | Analysis of impact metrics for the Protein Data Bank |
title_full | Analysis of impact metrics for the Protein Data Bank |
title_fullStr | Analysis of impact metrics for the Protein Data Bank |
title_full_unstemmed | Analysis of impact metrics for the Protein Data Bank |
title_short | Analysis of impact metrics for the Protein Data Bank |
title_sort | analysis of impact metrics for the protein data bank |
topic | Analysis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6190746/ https://www.ncbi.nlm.nih.gov/pubmed/30325351 http://dx.doi.org/10.1038/sdata.2018.212 |
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