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Non-Uniform and Absolute Minimal Sampling for High-Throughput Multidimensional NMR Applications

机译:高通量多维NMR应用的非均匀和绝对最小采样

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摘要

Many biomolecular NMR applications can benefit from the faster acquisition of multidimensional NMR data with high resolution and their automated analysis and interpretation. In recent years, a number of non-uniform sampling (NUS) approaches have been introduced for the reconstruction of multidimensional NMR spectra, such as compressed sensing, thereby bypassing traditional Fourier-transform processing. Such approaches are applicable to both biomacromolecules and small molecules and their complex mixtures and can be combined with homonuclear decoupling (pure shift) and covariance processing. For homonuclear 2D TOCSY experiments, absolute minimal sampling (AMS) permits the drastic shortening of measurement times necessary for high-throughput applications for identification and quantification of components in complex biological mixtures in the field of metabolomics. Such TOCSY spectra can be comprehensively represented by graph theoretical maximal cliques for the identification of entire spin systems and their subsequent query against NMR databases. Integration of these methods in webservers permits the rapid and reliable identification of mixture components. Recent progress is reviewed in this Minireview.
机译:许多生物分子NMR应用都可以从高分辨率的多维NMR数据及其自动分析和解释的更快获取中受益。近年来,已经引入了许多非均匀采样(NUS)方法来重建多维NMR光谱,例如压缩传感,从而绕过了传统的傅立叶变换处理。此类方法适用于生物大分子和小分子及其复杂混合物,并且可以与同核去耦(纯平移)和协方差处理结合使用。对于同核2D TOCSY实验,绝对最小采样(AMS)极大地缩短了代谢组学领域复杂生物混合物中成分的鉴定和定量所需的高通量应用所需的测量时间。这样的TOCSY光谱可以通过理论上最大的团簇来全面表示,以鉴定整个自旋系统并随后对NMR数据库进行查询。将这些方法集成到Web服务器中可以快速可靠地识别混合物成分。此Minireview审查了最新进展。

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