Analysis of impact metrics for the Protein Data Bank

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作者
Christopher Markosian
Luigi Di Costanzo
Monica Sekharan
Chenghua Shao
Stephen K. Burley
Christine Zardecki
机构
[1] School of Arts and Sciences,Department of Molecular Biology and Biochemistry
[2] Rutgers,undefined
[3] The State University of New Jersey,undefined
[4] RCSB Protein Data Bank,undefined
[5] Institute for Quantitative Biomedicine,undefined
[6] Rutgers,undefined
[7] The State University of New Jersey,undefined
[8] RCSB Protein Data Bank,undefined
[9] Skaggs School of Pharmacy and Pharmaceutical Sciences and San Diego Supercomputer Center,undefined
[10] University of California,undefined
[11] Cancer Institute of New Jersey,undefined
[12] Rutgers,undefined
[13] The State University of New Jersey,undefined
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摘要
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.
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