Circular dichroism spectroscopy is an important tool for determining the structural characteristics of biomolecules, particularly the secondary structure of proteins. In this paper we propose a Bayesian model that estimates the covariance structure within a measured spectrum and quantifies the uncertainty associated with the inferred secondary structures and characteristic spectra associated with each secondary structure type. Furthermore, we used tools from Bayesian model selection to determine the best secondary structure classification scheme and illustrate a technique for comparing whether or not two or more measured protein spectra share the same secondary structure. Our findings suggest that it is not possible to identify more than 3 distinct secondary structure classes from CD spectra above 175 nm. The inclusion of data from wavelengths between 175 and 200 nm did not substantially affect the ability to determine secondary structure fractions.

中文翻译：

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使用圆二色性数据进行蛋白质二级结构分析的贝叶斯推断评估–蛋白质圆二色性光谱中包含多少结构信息？

圆二色光谱是确定生物分子的结构特征，特别是蛋白质的二级结构的重要工具。在本文中，我们提出了一种贝叶斯模型，该模型可估计测量频谱内的协方差结构，并量化与推断的二级结构和与每种二级结构类型相关的特征谱相关的不确定性。此外，我们使用了来自贝叶斯模型选择的工具来确定最佳的二级结构分类方案，并说明了一种用于比较两个或多个测量的蛋白质光谱是否共享相同二级结构的技术。我们的发现表明，不可能从175 nm以上的CD光谱中识别出3种以上的不同二级结构。