BioMagResBank (BMRB) is designed to provide the scientific community with easy access to the wealth of data on biological macromolecules derived from solution-state NMR spectroscopy. Currently about 20% of new macromolecular structures are derived from NMR data, and BMRB is the unique resource worldwide designed to collect the underlying NMR data from these structures. BMRB also has the ability to archive quantitative data from the equally large set of published biomolecular NMR studies that, although not yielding complete three-dimensional coordinate sets, provide information at atomic resolution about local structure, dynamics, and chemical properties. It is envisioned that the availability of these data (local and global structure, parameters specifying local dynamics, local structural heterogeneity, pKa values, H-exchange rates, assigned chemical shifts, coupling constants, etc.) will facilitate our understanding of macromolecular structure and function and will catalyze the development of new avenues of research. Because BMRB is designed with an open architecture and maintains a relational database, it can respond quickly to changes in the biomolecular field (data types to be stored) and in standards for data exchange. BMRB has developed interoperability with the Protein Data Bank (PDB, Brookhaven) and the Nucleic Acid Database (NDB, Rutgers). BMRB has initiated collaborations with the newly funded Research Collaboratory for Structural Bioinformatics (RCSB or 'new PDB', Rutgers/NIST/San Diego Supercomputer Facility) and the European Bioinformatics Institute (EBI). The goal of these collaborations is to provide global access to a unified macromolecular structure database. The NMR component of this unified database, maintained at BMRB and mirrored elsewhere, will provide access to a wide range of data derived from macromolecular NMR investigations. The requested budget is that needed to enable BMRB to: (l) verify, reformat, archive, and distribute new data submitted electronically, (2) maintain a productive dialogue with the users and creators of biomolecular NMR data through interactions with individuals and with the BMRB Advisory Board, (3) collaborate with data banks specializing in x-ray crystallographic data and with software developers. The goal is to present users with a unified, global, macromolecular structure database that enables the broad scientific community to use this information in meaningful ways.
| Yokochi, Masashi; Kobayashi, Naohiro; Ulrich, Eldon L et al. (2016) Publication of nuclear magnetic resonance experimental data with semantic web technology and the application thereof to biomedical research of proteins. J Biomed Semantics 7:16 |
| Gutmanas, Aleksandras; Adams, Paul D; Bardiaux, Benjamin et al. (2015) NMR Exchange Format: a unified and open standard for representation of NMR restraint data. Nat Struct Mol Biol 22:433-4 |
| Tonelli, Marco; Eller, Chelcie H; Singarapu, Kiran K et al. (2015) Assignments of RNase A by ADAPT-NMR and enhancer. Biomol NMR Assign 9:81-8 |
| Sali, Andrej; Berman, Helen M; Schwede, Torsten et al. (2015) Outcome of the First wwPDB Hybrid/Integrative Methods Task Force Workshop. Structure 23:1156-67 |
| Berman, Helen M; Burley, Stephen K; Kleywegt, Gerard J et al. (2014) Response to On prompt update of literature references in the Protein Data Bank. Acta Crystallogr D Biol Crystallogr 70:2780 |
| Berman, Helen M; Kleywegt, Gerard J; Nakamura, Haruki et al. (2014) The Protein Data Bank archive as an open data resource. J Comput Aided Mol Des 28:1009-14 |
| Berman, Helen; Kleywegt, Gerard J; Nakamura, Haruki et al. (2013) Comment on on the propagation of errors by Jaskolski (2013). Acta Crystallogr D Biol Crystallogr 69:2297 |
| Berman, Helen M; Kleywegt, Gerard J; Nakamura, Haruki et al. (2013) The future of the Protein Data Bank. Biopolymers 99:218-22 |
| Berman, Helen M; Kleywegt, Gerard J; Nakamura, Haruki et al. (2013) How community has shaped the Protein Data Bank. Structure 21:1485-91 |
| Ellinger, James J; Chylla, Roger A; Ulrich, Eldon L et al. (2013) Databases and Software for NMR-Based Metabolomics. Curr Metabolomics 1: |
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