The CCPN data model for NMR spectroscopy: development of a software pipeline.

TitleThe CCPN data model for NMR spectroscopy: development of a software pipeline.
Publication TypeJournal Article
Year of Publication2005
AuthorsVranken, W. F., W. Boucher, T. J. Stevens, R. H. Fogh, A. Pajon, M. Llinas, E. L. Ulrich, J. L. Markley, J. Ionides, and E. D. Laue
JournalProteins
Volume59
Issue4
Pagination687-96
Date Published2005 Jun 1
ISSN1097-0134
KeywordsComputer Graphics, Databases, Protein, Magnetic Resonance Spectroscopy, Models, Theoretical, Software
Abstract

To address data management and data exchange problems in the nuclear magnetic resonance (NMR) community, the Collaborative Computing Project for the NMR community (CCPN) created a "Data Model" that describes all the different types of information needed in an NMR structural study, from molecular structure and NMR parameters to coordinates. This paper describes the development of a set of software applications that use the Data Model and its associated libraries, thus validating the approach. These applications are freely available and provide a pipeline for high-throughput analysis of NMR data. Three programs work directly with the Data Model: CcpNmr Analysis, an entirely new analysis and interactive display program, the CcpNmr FormatConverter, which allows transfer of data from programs commonly used in NMR to and from the Data Model, and the CLOUDS software for automated structure calculation and assignment (Carnegie Mellon University), which was rewritten to interact directly with the Data Model. The ARIA 2.0 software for structure calculation (Institut Pasteur) and the QUEEN program for validation of restraints (University of Nijmegen) were extended to provide conversion of their data to the Data Model. During these developments the Data Model has been thoroughly tested and used, demonstrating that applications can successfully exchange data via the Data Model. The software architecture developed by CCPN is now ready for new developments, such as integration with additional software applications and extensions of the Data Model into other areas of research.

DOI10.1002/prot.20449
Alternate JournalProteins
PubMed ID15815974
Grant ListGM67965 / GM / NIGMS NIH HHS / United States
P41 LM005799 / LM / NLM NIH HHS / United States
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