Steinbach Peter J, Ionescu Roxana, Matthews C Robert
Center for Molecular Modeling, Center for Information Technology, National Institutes of Health, Bethesda, Maryland 20892, USA.
Biophys J. 2002 Apr;82(4):2244-55. doi: 10.1016/S0006-3495(02)75570-7.
A hybrid analysis that combines the maximum entropy method (MEM) with nonlinear least squares (NLS) fitting has been developed to interpret a general time-dependent signal. Data that include processes of opposite sign and a slow baseline drift can be inverted to obtain both a continuous distribution of lifetimes and a sum of discrete exponentials. Fits by discrete exponentials are performed with initial parameters determined from the distribution of lifetimes obtained with the MEM. The regularization of the parameter space achieved by the MEM stabilizes the introduction of each successive exponential in the NLS fits. This hybrid approach is particularly useful when fitting by a large number of exponentials. Revision of the MEM "prior" based on features in the data can improve the lifetime distribution obtained. Standard errors in the mean are estimated automatically for raw data. The results presented for simulated data and for fluorescence measurements of protein folding illustrate the utility and accuracy of the hybrid algorithm. Analysis of the folding of dihydrofolate reductase reveals six kinetic processes, one more than previously reported.
已开发出一种将最大熵方法（MEM）与非线性最小二乘法（NLS）拟合相结合的混合分析方法，用于解释一般的随时间变化的信号。包含相反符号过程和缓慢基线漂移的数据可以进行反演，以获得寿命的连续分布和离散指数之和。离散指数拟合使用从MEM获得的寿命分布确定的初始参数进行。MEM实现的参数空间正则化稳定了NLS拟合中每个连续指数的引入。当用大量指数进行拟合时，这种混合方法特别有用。基于数据中的特征对MEM“先验”进行修正可以改善获得的寿命分布。会自动估计原始数据均值的标准误差。给出的模拟数据和蛋白质折叠荧光测量结果说明了混合算法的实用性和准确性。对二氢叶酸还原酶折叠的分析揭示了六个动力学过程，比之前报道的多一个。
