The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
RCSB Protein Data Bank: Sustaining a living digital data resource that enables breakthroughs in scientific research and biomedical education
Open accessAbstract
The Protein Data Bank (PDB) is one of two archival resources for experimental data central to biomedical research and education worldwide (the other key Primary Data Archive in biology being the International Nucleotide Sequence Database Collaboration). The PDB currently houses >134,000 atomic level biomolecular structures determined by crystallography, NMR spectroscopy, and 3D electron microscopy. It was established in 1971 as the first open‐access, digital‐data resource in biology, and is managed by the Worldwide Protein Data Bank partnership (wwPDB; wwpdb.org). US PDB operations are conducted by the RCSB Protein Data Bank (RCSB PDB; RCSB.org; Rutgers University and UC San Diego) and funded by NSF, NIH, and DoE. The RCSB PDB serves as the global Archive Keeper for the wwPDB. During calendar 2016, >591 million structure data files were downloaded from the PDB by Data Consumers working in every sovereign nation recognized by the United Nations. During this same period, the RCSB PDB processed >5300 new atomic level biomolecular structures plus experimental data and metadata coming into the archive from Data Depositors working in the Americas and Oceania. In addition, RCSB PDB served >1 million RCSB.org users worldwide with PDB data integrated with ∼40 external data resources providing rich structural views of fundamental biology, biomedicine, and energy sciences, and >600,000 PDB101.rcsb.org educational website users around the globe. RCSB PDB resources are described in detail together with metrics documenting the impact of access to PDB data on basic and applied research, clinical medicine, education, and the economy.
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Cites
The FAIR Guiding Principles for scientific data management and stewardship
Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J.-W., da Silva Santos, L. B., Bourne, P. E., et al. (2016) · Scientific Data · doi:10.1038/sdata.2016.18 · Cited by 18,423
Molecular Structure of Nucleic Acids: A Structure for Deoxyribose Nucleic Acid
WATSON, J. D., & CRICK, F. H. C. (1953) · Nature · doi:10.1038/171737a0 · Cited by 13,584
Announcing the worldwide Protein Data Bank
Berman, H., Henrick, K., & Nakamura, H. (2003) · Nature Structural & Molecular Biology · doi:10.1038/nsb1203-980 · Cited by 3,093
Self-citationPrinciples of protein-protein interactions
Jones, S., & Thornton, J. M. (1996) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.93.1.13 · Cited by 2,684
NGL Viewer: a web application for molecular visualization
Rose, A. S., & Hildebrand, P. W. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv402 · Cited by 462
Cited by
The Transporter Classification Database (TCDB): 2021 update
Saier, M. H., Reddy, V. S., Moreno-Hagelsieb, G., Hendargo, K. J., Zhang, Y., Iddamsetty, V., Lam, K. J. K., Tian, N., Russum, S., Wang, J., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1004 · Cited by 467
DPAM : A domain parser for AlphaFold models
(2022) · doi:10.1002/pro.4548 · Cited by 49
CASP13 target classification into tertiary structure prediction categories
Kinch, L. N., Kryshtafovych, A., Monastyrskyy, B., & Grishin, N. V. (2019) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.25775 · Cited by 36
Critical assessment of coiled-coil predictions based on protein structure data
Simm, D., Hatje, K., Waack, S., & Kollmar, M. (2021) · Scientific Reports · doi:10.1038/s41598-021-91886-w · Cited by 24
Structural insights into pink-eyed dilution protein (Oca2)
Mesdaghi, S., Murphy, D. L., Simpkin, A. J., & Rigden, D. J. (2023) · Bioscience Reports · doi:10.1042/bsr20230060 · Cited by 13
Metadata
- Authors
- Burley, S. K., Berman, H. M., Christie, C., Duarte, J. M., Feng, Z., Westbrook, J., Young, J., & Zardecki, C.
- Venue
- Protein Science
- Publisher
- Wiley
- Published
- 2017-11-11
- Volume
- 27
- Issue
- 1
- Pages
- 316-330
- ISSN
- 0961-8368 (ISSN-L)
- 1469-896X
- OpenAlex
- W2766737008
- Cited by
- 293
- References
- 5
- FWCI
- 52.98
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Burley, S. K., Berman, H. M., Christie, C., Duarte, J. M., Feng, Z., Westbrook, J., Young, J., & Zardecki, C. (2018). RCSB Protein Data Bank: Sustaining a living digital data resource that enables breakthroughs in scientific research and biomedical education. Protein Science. https://doi.org/10.1002/pro.3331
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.