Related ArticlesFast multi-dimensional NMR acquisition and processing using the sparse FFT.
J Biomol NMR. 2015 Sep;63(1):9-19
Authors: Hassanieh H, Mayzel M, Shi L, Katabi D, Orekhov VY
Abstract
Increasing the dimensionality of NMR experiments strongly enhances the spectral resolution and provides invaluable direct information about atomic interactions. However, the price tag is high: long measurement times and heavy requirements on the computation power and data storage. We introduce sparse fast Fourier transform as a new method of NMR signal collection and processing, which is capable of reconstructing high quality spectra of large size and dimensionality with short measurement times, faster computations than the fast Fourier transform, and minimal storage for processing and handling of sparse spectra. The new algorithm is described and demonstrated for a 4D BEST-HNCOCA spectrum.
Fast multi-dimensional NMR acquisition and processing using the sparse FFT
Fast multi-dimensional NMR acquisition and processing using the sparse FFT
Abstract
Increasing the dimensionality of NMR experiments strongly enhances the spectral resolution and provides invaluable direct information about atomic interactions. However, the price tag is high: long measurement times and heavy requirements on the computation power and data storage. We introduce sparse fast Fourier transform as a new method of NMR signal collection and processing, which is capable of reconstructing high quality spectra of large size and dimensionality...
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06-30-2015 11:41 AM
[Question from NMRWiki Q&A forum] How to performing acquisition during all time multi pulse sequence - Bruker ?
How to performing acquisition during all time multi pulse sequence - Bruker ?
Hi all, I have a small question on how to aquired a complete signal in BRUKER AVIII.I want to create a multi pulse sequence (1D), where I want to aquire the signal (sequentially) do not adding or replacing the data before each pulse.
||__________||_________||__________||___________ ...
tp tp tp tp ...Performing Aquisition all time.................
|| - pulse
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10-10-2013 09:27 AM
[NMR paper] Rapid prediction of multi-dimensional NMR data sets.
Rapid prediction of multi-dimensional NMR data sets.
http://www.bionmr.com//www.ncbi.nlm.nih.gov/corehtml/query/egifs/http:--production.springer.de-OnlineResources-Logos-springerlink.gif Related Articles Rapid prediction of multi-dimensional NMR data sets.
J Biomol NMR. 2012 Dec;54(4):377-87
Authors: Gradmann S, Ader C, Heinrich I, Nand D, Dittmann M, Cukkemane A, van Dijk M, Bonvin AM, Engelhard M, Baldus M
Abstract
We present a computational environment for Fast Analysis of multidimensional NMR DAta Sets (FANDAS) that allows assembling...
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05-15-2013 03:12 PM
Parallel acquisition of multi-dimensional spectra in protein NMR
Parallel acquisition of multi-dimensional spectra in protein NMR
Abstract We introduce the use of multiple receivers applied in parallel for simultaneously recording multi-dimensional data sets of proteins in a single experiment. The utility of the approach is established through the introduction of the 2D 15N,1HN||13CO HSQC experiment in which a pair of two-dimensional 15N,1HN and 15N,13CO spectra are recorded. The methodology is further extended to higher dimensionality via the 3D 1HN||13CO HNCA in which a pair of data sets recording 13Cα,15N,1HN and 13Cα,15N,13CO chemical shifts...
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07-20-2012 11:13 PM
Al NMR: a novel NMR data processing program optimized for sparse sampling
Al NMR: a novel NMR data processing program optimized for sparse sampling
Abstract Sparse sampling in biomolecular multidimensional NMR offers increased acquisition speed and resolution and, if appropriate conditions are met, an increase in sensitivity. Sparse sampling of indirectly detected time domains combined with the direct truly multidimensional Fourier transform has elicited particular attention because of the ability to generate a final spectrum amenable to traditional analysis techniques. A number of sparse sampling schemes have been described including radial sampling, random...
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11-17-2011 01:47 AM
Fast NMR Data Acquisition From Bicelles Containing a Membrane-Associated Peptide at Natural-Abundance.
Fast NMR Data Acquisition From Bicelles Containing a Membrane-Associated Peptide at Natural-Abundance.
Fast NMR Data Acquisition From Bicelles Containing a Membrane-Associated Peptide at Natural-Abundance.
J Phys Chem B. 2011 Sep 22;
Authors: Yamamoto K, Vivekanandan S, Ramamoorthy A
Abstract
In spite of recent technological advances in NMR spectroscopy, its low sensitivity continues to be a major limitation particularly for the structural studies of membrane proteins. The need for a large quantity of a membrane protein and acquisition of...
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09-24-2011 04:11 PM
[NMR paper] Fast multi-dimensional NMR of proteins.
Fast multi-dimensional NMR of proteins.
Related Articles Fast multi-dimensional NMR of proteins.
J Biomol NMR. 2003 Apr;25(4):349-54
Authors: Kupce E, Freeman R
Three-dimensional HNCO and HNCA subspectra from a small protein (agitoxin, 4 kDa, enriched in carbon-13 and nitrogen-15), have been obtained by direct frequency-domain excitation of selected carbon and nitrogen sites. This new technique applies an array of several simultaneous soft radiofrequency spin-inversion pulses, encoded (on or off) according to nested Hadamard matrices, and the...
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11-24-2010 09:01 PM
Combining methods for speeding up multi-dimensional acquisition. Sparse sampling and
Combining methods for speeding up multi-dimensional acquisition. Sparse sampling and fast pulsing methods for unfolded proteins
Publication year: 2010
Source: Journal of Magnetic Resonance, In Press, Accepted Manuscript, Available online 12 June 2010</br>
Dominique, Marion</br>
Resonance assignment of intrinsically disordered proteins is made difficult by the extensive spectral overlaps. High-resolution 3D and 4D spectra are thus essential for this purpose. We have adapted the series of 3D BEST experiments proposed by Lescop et al to the case of unfolded proteins. Longer acquisitions...
Fast multi-dimensional NMR acquisition and processing using the sparse FFT.
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