Mathematical Sciences: Multilinear Analysis of SpectroscopicData

数学科学：光谱数据的多线性分析

• 批准号: 8902265
• 负责人: Sue Leurgans
• 金额: $ 12.67万
• 依托单位: Ohio State University
• 依托单位国家: 美国
• 项目类别: Continuing grant
• 财政年份: 1989
• 资助国家: 美国
• 起止时间: 1989-07-01 至 1993-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8902265&HistoricalAwards=false
• 关键词: Mathematical; Sciences; Multilinear; Analysis; SpectroscopicData

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.

主要研究人员将进行交叉研究 学科性质，涵盖统计学和生物物理学 领域的 他们将研究光谱及其变化， 对试样条件变化的响应，以便 确定有关的组成部分的重要信息 试样 例如，芳香族氨基酸的荧光 蛋白质结构的有用探针。 经常，“在 vivo的研究和其他重要的实验涉及一个单一的 包含多个重叠成分的样本 光谱，不能分离的组分， 改变天然样本的性质。 调查人员 我们将努力实现三个目标： 解析组分光谱的统计方法，发展 高效可靠的算法和计算机代码， 实施所制定的方法，并应用这些方法 在实验室