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Default Iterative algorithm of discrete Fourier transform for processing randomly sampled NMR

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.
  • Content Type Journal Article
  • DOI 10.1007/s10858-010-9411-2
  • Authors
    • Jan Stanek, University of Warsaw Faculty of Chemistry Pasteura 1 02-093 Warsaw Poland
    • Wiktor Ko┼║mi┼?ski, University of Warsaw Faculty of Chemistry Pasteura 1 02-093 Warsaw Poland

Source: Journal of Biomolecular NMR
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