Journal of Biomolecular NMR

, Volume 47, Issue 1, pp 65–77 | Cite as

Iterative algorithm of discrete Fourier transform for processing randomly sampled NMR data sets

Article

Abstract

Spectra obtained by application of multidimensional Fourier Transformation (MFT) to sparsely sampled nD NMR signals are usually corrupted due to missing data. In the present paper this phenomenon is investigated on simulations and experiments. An effective iterative algorithm for artifact suppression for sparse on-grid NMR data sets is discussed in detail. It includes automated peak recognition based on statistical methods. The results enable one to study NMR spectra of high dynamic range of peak intensities preserving benefits of random sampling, namely the superior resolution in indirectly measured dimensions. Experimental examples include 3D 15N- and 13C-edited NOESY-HSQC spectra of human ubiquitin.

Keywords

Multidimensional NMR spectroscopy Fourier transformation Sparse sampling Random sampling NOESY Proteins Ubiquitin 

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Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.Faculty of ChemistryUniversity of WarsawWarsawPoland

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