Mathematical Sciences: Multilinear Analysis of SpectroscopicData

首席研究人员将进行跨学科性质的研究，涉及统计学和生物物理学两个领域。他们将研究光谱及其随样品条件变化的变化，以确定有关样品成分的重要信息。例如，来自芳香族氨基酸的荧光是蛋白质结构的有用探针。通常，体内研究和其他重要实验涉及单个样品，其中包含多个光谱重叠的成分，如果不严重改变本地样品的性质，这些成分就无法分离。研究人员将朝着三个目标努力：开发解析组分光谱的最佳统计方法，开发执行所开发方法的高效和可靠的算法和计算机代码，以及在实验室应用这些方法。

The principal investigators will conduct research of a cross disciplinary nature, spanning both statistics and biophysics fields. They will investigate the spectra and their changes in response to variation in the conditions of a specimen in order to ascertain important information about the components of a specimen. For example, fluorescence from aromatic amino acids is a useful probe of the structure of proteins. Frequently, 'in vivo' studies and other important experiments concern a single specimen that contains multiple components with overlapping spectra, components that cannot be separated without seriously altering properties of the native specimen. The investigators will work toward three goals: the development of optimal statistical methods of resolving component spectra, development of efficient and reliable algorithms and computer codes that implement the methods developed, and application of these methods in the laboratory.