Anand Christopher Kumar, Bain Alex D, Sharma Anuroop
Department of Computing and Software, McMaster University, 1280 Main Street West, ITB-202, Hamilton, Ont., Canada L8S 4K1.
J Magn Reson. 2009 Mar;197(1):63-70. doi: 10.1016/j.jmr.2008.12.005. Epub 2008 Dec 13.
Non-uniform sampling in multidimensional NMR shows great promise to significantly decrease experimental acquisition times, especially for relaxation experiments for which peak locations are already known. In this paper we present a method for optimizing the non-uniform sampling points such that the noise amplification and numerical instabilities are minimized. In particular, the minimum singular value of the Moore-Penrose pseudo-inverse is maximized using sequential semi-definite programming, thereby minimizing the worst-case errors. We test this method numerically on a set of assignment data from the proteins ubiquitin (in both folded and unfolded states) and RIalpha (119-244), a cAMP-binding regulatory subunit of protein kinase A (PKA). This test indicates that optimizing more than doubles the efficiency over random selection of points, and the efficiency increases as we go to higher dimensions.
多维核磁共振中的非均匀采样在显著减少实验采集时间方面显示出巨大潜力，特别是对于那些峰位置已知的弛豫实验。在本文中，我们提出了一种优化非均匀采样点的方法，以使噪声放大和数值不稳定性最小化。特别是，使用顺序半定规划使摩尔 - 彭罗斯伪逆的最小奇异值最大化，从而将最坏情况误差最小化。我们在一组来自蛋白质泛素（折叠和未折叠状态）以及RIalpha（119 - 244）的数据上进行了数值测试，RIalpha是蛋白激酶A（PKA）的一种cAMP结合调节亚基。该测试表明，与随机选择点相比，优化后的效率提高了一倍多，并且随着维度的增加效率也会提高。
