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A general Bayesian method for an automated signal class recognition in 2D NMR spectra combined with a multivariate discriminant analysis

Antz, C. and Neidig, K.-P. and Kalbitzer, Hans Robert (1995) A general Bayesian method for an automated signal class recognition in 2D NMR spectra combined with a multivariate discriminant analysis. Journal of Biomolecular NMR 5 (3), pp. 287-296.

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Abstract

A generally applicable method for the automated classification of 2D NMR peaks has been developed, based on a Bayesian approach coupled to a multivariate linear discriminant analysis of the data. The method can separate true NMR signals from noise signals, solvent stripes and artefact signals. The analysis relies on the assumption that the different signal classes have different distributions of ...

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Item Type:Article
Date:1995
Institutions:Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Dr. Hans Robert Kalbitzer
Identification Number:
ValueType
10.1007/BF00211755DOI
Keywords:Multivariate discriminant analysis - 2D NMR spectroscopy - NOESY - Bayesian analysis - Peak recognition - NMR molecular structure
Subjects:500 Science > 570 Life sciences
Status:Published
Refereed:Unknown
Created at the University of Regensburg:Unknown
Owner: Gertraud Kellers
Deposited On:08 Sep 2010 07:59
Last Modified:08 Sep 2010 07:59
Item ID:16514
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