The Experts below are selected from a list of 147 Experts worldwide ranked by ideXlab platform
V A Chertkov - One of the best experts on this subject based on the ideXlab platform.
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total lineshape analysis of high resolution NMR Spectra powered by simulated annealing
Journal of Magnetic Resonance, 2016Co-Authors: D.a. Cheshkov, D. O. Sinitsyn, K F Sheberstov, V A ChertkovAbstract:The novel algorithm for a total lineshape analysis of high-resolution NMR Spectra has been developed. A global optimization by simulated annealing has been applied that has allowed to overcome the main trouble of common approaches which had frequently returned solutions for local minima rather than for global ones. The algorithm has been verified for the four-spin test systems ABCD, and has been successfully used for analysis of experimental NMR Spectra of proline. The approach has allowed to avoid a sophisticated manual setup of initial parameters and to conduct the analysis of complicated high-resolution NMR Spectra nearly automatically.
D.a. Cheshkov - One of the best experts on this subject based on the ideXlab platform.
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Total line shape analysis of high-resolution NMR Spectra
Annual Reports on NMR Spectroscopy, 2020Co-Authors: D.a. Cheshkov, D. O. SinitsynAbstract:Abstract Analysis of high-resolution NMR Spectra consist in determining the parameters of the spin system that provide the best correspondence between the theoretical and experimental Spectra. This review is devoted to modern approaches to the total line shape analysis of high-resolution NMR Spectra; discussion of difficulties and pitfalls associated with both the fundamental features of high-resolution NMR Spectra and the optimization of parameters values. The question of the accuracy of determining values of spin systems parameters is discussed. Practical examples of the Spectra analysis are considered, as well as recommendations for obtaining experimental NMR Spectra of high quality.
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total lineshape analysis of high resolution NMR Spectra powered by simulated annealing
Journal of Magnetic Resonance, 2016Co-Authors: D.a. Cheshkov, D. O. Sinitsyn, K F Sheberstov, V A ChertkovAbstract:The novel algorithm for a total lineshape analysis of high-resolution NMR Spectra has been developed. A global optimization by simulated annealing has been applied that has allowed to overcome the main trouble of common approaches which had frequently returned solutions for local minima rather than for global ones. The algorithm has been verified for the four-spin test systems ABCD, and has been successfully used for analysis of experimental NMR Spectra of proline. The approach has allowed to avoid a sophisticated manual setup of initial parameters and to conduct the analysis of complicated high-resolution NMR Spectra nearly automatically.
K F Sheberstov - One of the best experts on this subject based on the ideXlab platform.
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total lineshape analysis of high resolution NMR Spectra powered by simulated annealing
Journal of Magnetic Resonance, 2016Co-Authors: D.a. Cheshkov, D. O. Sinitsyn, K F Sheberstov, V A ChertkovAbstract:The novel algorithm for a total lineshape analysis of high-resolution NMR Spectra has been developed. A global optimization by simulated annealing has been applied that has allowed to overcome the main trouble of common approaches which had frequently returned solutions for local minima rather than for global ones. The algorithm has been verified for the four-spin test systems ABCD, and has been successfully used for analysis of experimental NMR Spectra of proline. The approach has allowed to avoid a sophisticated manual setup of initial parameters and to conduct the analysis of complicated high-resolution NMR Spectra nearly automatically.
D. O. Sinitsyn - One of the best experts on this subject based on the ideXlab platform.
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Total line shape analysis of high-resolution NMR Spectra
Annual Reports on NMR Spectroscopy, 2020Co-Authors: D.a. Cheshkov, D. O. SinitsynAbstract:Abstract Analysis of high-resolution NMR Spectra consist in determining the parameters of the spin system that provide the best correspondence between the theoretical and experimental Spectra. This review is devoted to modern approaches to the total line shape analysis of high-resolution NMR Spectra; discussion of difficulties and pitfalls associated with both the fundamental features of high-resolution NMR Spectra and the optimization of parameters values. The question of the accuracy of determining values of spin systems parameters is discussed. Practical examples of the Spectra analysis are considered, as well as recommendations for obtaining experimental NMR Spectra of high quality.
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total lineshape analysis of high resolution NMR Spectra powered by simulated annealing
Journal of Magnetic Resonance, 2016Co-Authors: D.a. Cheshkov, D. O. Sinitsyn, K F Sheberstov, V A ChertkovAbstract:The novel algorithm for a total lineshape analysis of high-resolution NMR Spectra has been developed. A global optimization by simulated annealing has been applied that has allowed to overcome the main trouble of common approaches which had frequently returned solutions for local minima rather than for global ones. The algorithm has been verified for the four-spin test systems ABCD, and has been successfully used for analysis of experimental NMR Spectra of proline. The approach has allowed to avoid a sophisticated manual setup of initial parameters and to conduct the analysis of complicated high-resolution NMR Spectra nearly automatically.
D. Flemming Hansen - One of the best experts on this subject based on the ideXlab platform.
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Using Deep Neural Networks to Reconstruct Non-uniformly Sampled NMR Spectra
Journal of Biomolecular NMR, 2019Co-Authors: D. Flemming HansenAbstract:Non-uniform and sparse sampling of multi-dimensional NMR Spectra has over the last decade become an important tool to allow for fast acquisition of multi-dimensional NMR Spectra with high resolution. The success of non-uniform sampling NMR hinge on both the development of algorithms to accurately reconstruct the sparsely sampled Spectra and the design of sampling schedules that maximise the information contained in the sampled data. Traditionally, the reconstruction tools and algorithms have aimed at reconstructing the full spectrum and thus ‘fill out the missing points’ in the time-domain spectrum, although other techniques are based on multi-dimensional decomposition and extraction of multi-dimensional shapes. Also over the last decade, machine learning, deep neural networks, and artificial intelligence have seen new applications in an enormous range of sciences, including analysis of MRI Spectra. As a proof-of-principle, it is shown here that simple deep neural networks can be trained to reconstruct sparsely sampled NMR Spectra. For the reconstruction of two-dimensional NMR Spectra, reconstruction using a deep neural network performs as well, if not better than, the currently and widely used techniques. It is therefore anticipated that deep neural networks provide a very valuable tool for the reconstruction of sparsely sampled NMR Spectra in the future to come.
