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The Protein Data Bank and lessons in data management
Philip E Bourne1, John Westbrook, Helen M Berman
1Department of Pharmacology and San Diego Supercomputer Center, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0537, USA. bourne@sdsc.edu
Briefings in Bioinformatics
|May 22, 2004
Summary
The Protein Data Bank (PDB), a key macromolecular structure database, offers valuable lessons for biological database developers. Best practices emphasize data quality, representation, IT support, and the crucial human element.
Area of Science:
- Structural Biology
- Bioinformatics
- Computational Biology
Background:
- The Protein Data Bank (PDB) has a long-standing history as a critical resource for macromolecular structures.
- Understanding the PDB's evolution provides insights into the development of biological databases.
Observation:
- The PDB's development highlights the importance of data quality, representation, and supporting information technology.
- Non-data and technology challenges are significant factors in database management.
- The human element, including users, collaborators, and scientific committees, plays a vital role.
Findings:
- Lessons learned from the PDB's history inform current best practices for biological database development.
- A holistic approach is necessary, integrating data management, technological infrastructure, and human collaboration.
- Effective biological databases require continuous adaptation and consideration of diverse stakeholder needs.
Implications:
- Adopting PDB's best practices can enhance the reliability and utility of emerging biological databases.
- This historical perspective offers a roadmap for creating robust and sustainable biological data resources.
- Improved database development benefits the broader scientific community by facilitating research and discovery.