Monte Carlo analysis of sedimentation experiments

被引:102
作者
Demeler, Borries [1 ]
Brookes, Emre [2 ]
机构
[1] Univ Texas Hlth Sci Ctr San Antonio, Dept Biochem, San Antonio, TX 78229 USA
[2] Univ Texas San Antonio, Dept Comp Sci, San Antonio, TX USA
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
two-dimensional spectrum analysis; genetic algorithms; UltraScan; analytical ultracentrifugation; molecular weight determination; curve fitting;
D O I
10.1007/s00396-007-1699-4
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
High resolution analysis approaches for sedimentation experiments have recently been developed that promise to provide a detailed description of heterogeneous samples by identifying both shape and molecular weight distributions. In this study, we describe the effect experimental noise has on the accuracy and precision of such determinations and offer a stochastic Monte Carlo approach, which reliably quantifies the effect of noise by determining the confidence intervals for the parameters that describe each solute. As a result, we can now predict reliable confidence intervals for determined parameters. We also explore the effect of various experimental parameters on the confidence intervals and provide suggestions for improving the statistics by applying a few practical rules for the design of sedimentation experiments.
引用
收藏
页码:129 / 137
页数:9
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