title: Iterative algorithm of discrete Fourier transform for processing randomly sampled NMR data sets.
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 (15)N- and (13)C-edited NOESY-HSQC spectra of human ubiquitin.
authors.affiliation: Faculty of Chemistry, University of Warsaw, Pasteura 1, 02-093, Warsaw, Poland.
authors.forename: Jan
authors.initials: J
authors.lastname: Stanek
authors.forename: Wiktor
authors.initials: W
authors.lastname: Koźmiński
mesh_terms: D000465:Algorithms; D002247:Carbon Isotopes / Q000737:chemistry; D016208:Databases, Factual; D005583:Fourier Analysis; D006801:Humans; D009587:Nitrogen Isotopes / Q000737:chemistry; D019906:Nuclear Magnetic Resonance, Biomolecular / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D025801:Ubiquitin / Q000737:chemistry
chemical_list: D002247:Carbon Isotopes; D009587:Nitrogen Isotopes; D025801:Ubiquitin