Abstract
A method for five-dimensional spectral reconstruction of non-uniformly sampled NMR data sets is proposed. It is derived from the previously published signal separation algorithm, with major alterations to avoid unfeasible processing of an entire five-dimensional spectrum. The proposed method allows credible reconstruction of spectra from as little as a few hundred data points and enables sensitive resonance detection in experiments with a high dynamic range of peak intensities. The efficiency of the method is demonstrated on two high-resolution spectra for rapid sequential assignment of intrinsically disordered proteins, namely 5D HN(CA)CONH and 5D (HACA)CON(CO)CONH.
PMID: 28243768 [PubMed - as supplied by publisher]
Reconstruction of non-uniformly sampled five-dimensional NMR spectra by signal separation algorithm
Reconstruction of non-uniformly sampled five-dimensional NMR spectra by signal separation algorithm
Abstract
A method for five-dimensional spectral reconstruction of non-uniformly sampled NMR data sets is proposed. It is derived from the previously published signal separation algorithm, with major alterations to avoid unfeasible processing of an entire five-dimensional spectrum. The proposed method allows credible reconstruction of spectra from as little as a few hundred data points and enables sensitive resonance detection in experiments with a high...
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03-01-2017 04:13 AM
Sparse multidimensional iterative lineshape-enhanced (SMILE) reconstruction of both non-uniformly sampled and conventional NMR data
Sparse multidimensional iterative lineshape-enhanced (SMILE) reconstruction of both non-uniformly sampled and conventional NMR data
Abstract
Implementation of a new algorithm, SMILE, is described for reconstruction of non-uniformly sampled two-, three- and four-dimensional NMR data, which takes advantage of the known phases of the NMR spectrum and the exponential decay of underlying time domain signals. The method is very robust with respect to the chosen sampling protocol and, in its default mode, also extends the truncated time domain signals by a...
Analysis of non-uniformly sampled spectra with multi-dimensional decomposition
Analysis of non-uniformly sampled spectra with multi-dimensional decomposition
Publication year: 2011
Source:Progress in Nuclear Magnetic Resonance Spectroscopy, Volume 59, Issue 3</br>
Vladislav Yu. Orekhov, Victor A. Jaravine</br>
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03-09-2012 09:16 AM
Suppression of sampling artefacts in high-resolution four-dimensional NMR spectra using Signal Separation Algorithm
Suppression of sampling artefacts in high-resolution four-dimensional NMR spectra using Signal Separation Algorithm
Publication year: 2011
Source: Journal of Magnetic Resonance, Available online 20 October 2011</br>
Jan*Stanek, Rafal*Augustyniak, Wiktor*Ko?mi?ski</br>
The development of non-uniform sampling (NUS) strategies permits to obtain high-dimensional spectra with increased resolution in significantly reduced experimental time. We extended a previously proposed signal separation algorithm (SSA) to process sparse four-dimensional NMR data. It is employed for two experiments...
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10-22-2011 10:16 AM
Analysis of non-uniformly sampled spectra with Multi-Dimensional Decomposition
Analysis of non-uniformly sampled spectra with Multi-Dimensional Decomposition
Publication year: 2011
Source: Progress in Nuclear Magnetic Resonance Spectroscopy, In Press, Accepted Manuscript, Available online 24 February 2011</br>
Vladislav Yu., Orekhov , Victor A., Jaravine</br>
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02-26-2011 01:07 PM
FM reconstruction of non-uniformly sampled protein NMR data at higher dimensions and optimization by distillation
FM reconstruction of non-uniformly sampled protein NMR data at higher dimensions and optimization by distillation
Abstract Non-uniform sampling (NUS) enables recording of multidimensional NMR data at resolutions matching the resolving power of modern instruments without using excessive measuring time. However, in order to obtain satisfying results, efficient reconstruction methods are needed. Here we describe an optimized version of the Forward Maximum entropy (FM) reconstruction method, which can reconstruct up to three indirect dimensions. For complex datasets, such as NOESY spectra,...