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

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.

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Rieping, W, Autor
Habeck, M1, Autor           
Nilges, M, Autor
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              

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 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.

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 Datum: 2005-11
 Publikationsstatus: Erschienen
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Titel: J. Am. Chem. Soc.
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 127 Artikelnummer: - Start- / Endseite: 16026 - 16027 Identifikator: -