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Modeling Errors in NOE Data with a Log-normal Distribution Improves the Quality of NMR Structures

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons83949

Habeck,  M
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Rieping, W., Habeck, M., & Nilges, M. (2005). Modeling Errors in NOE Data with a Log-normal Distribution Improves the Quality of NMR Structures. J. Am. Chem. Soc., 127, 16026-16027. Retrieved from http://www.bio.cam.ac.uk/zope/isd/publications/lognormal_2005.pdf/view.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-D385-4
Zusammenfassung
The distribution of the deviation of calculated from measured nuclear Overhauser effect (NOE) intensities is a priori unknown. The use of a log-normal distribution to describe these deviations permits the direct calculation of a structure from the measured intensities without first converting them into distance bounds. We show that the log-normal distribution is a natural choice for describing errors in NOE data and that it improves the accuracy, precision, and quality of the calculated structures compared to the usual bounds representation.