Comparative Visualization and Analysis for GCxGC

GCxGC 的比较可视化和分析

• 批准号: 7108315
• 负责人: Qingping Tao
• 金额: $ 23.94万
• 依托单位: GC IMAGE, LLC
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-01 至 2008-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7108315
• 关键词: classification; sectioning

DESCRIPTION (provided by applicant): This project will investigate and develop effective information technologies for comparative analysis and visualization of complex data generated by comprehensive two-dimensional gas chromatography (GCxGC). GCxGC is an emerging technology that provides an order-of-magnitude greater separation capacity, significantly better signal-to-noise ratio, and higher dimensional retention-structure relations than traditional GC. The principal challenge for utilization of GCxGC, in a wide range of public-health and other applications, is the difficulty of analyzing and interpreting the large, complex data it generates. The quantity and complexity of GCxGC data necessitates the investigation and development of new information technologies. This project will develop and demonstrate innovative methods and tools for comparative analysis of GCxGC datasets. The expected results of this research and development include a PCA-based method for chemical fingerprinting, decision trees with chemical constraints for sample classification, genetic programming for template and constraint-based matching and classification, and visualization methods for comparative GCxGC analyses. These methods will be implemented in commercial software that will support researchers and laboratory analysts in a wide range of commercial applications, including health care, environmental monitoring, and chemical processing. The power of GCxGC, supported by effective information technologies, will enable better understanding of chemical compositions and processes, a foundation for future scientific advances and discoveries. Relevance to Public Health. Today, a few advanced laboratories are pioneering GCxGC for a variety of applications such as environmental monitoring of exposure profiles in air, soil, food, and water; identification and quantification of toxic products in blood, urine, milk, and breath samples; and qualitative and quantitative metabolomics to provide a holistic view of the biochemical status or biochemical phenotype of an organism. Many analyses in these applications require detailed chemical comparisons of samples, e.g..monitoring changes, comparison to reference standards, chemical matching or "fingerprinting", and classification. GCxGC is a powerful new technology for such comparative analyses. This proposal will provide innovative information technologies to support users in these applications.

描述(申请人提供)：该项目将研究和开发有效的信息技术，用于对综合二维气相色谱(GCxGC)产生的复杂数据进行比较分析和可视化。GCxGC是一种新兴技术，它提供了比传统GC更大的分离能力、显著更好的信噪比和更高维度的保留-结构关系。在广泛的公共卫生和其他应用中使用GCxGC的主要挑战是分析和解释它产生的大量复杂数据的困难。GCxGC数据的数量和复杂性要求研究和开发新的信息技术。该项目将开发和展示GCxGC数据集比较分析的创新方法和工具。这一研究和开发的预期结果包括基于主成分分析的化学指纹识别方法，用于样品分类的带有化学约束的决策树，用于模板和基于约束的匹配和分类的遗传编程，以及用于比较GCxGC分析的可视化方法。这些方法将在商业软件中实施，这些软件将在广泛的商业应用中支持研究人员和实验室分析人员，包括医疗保健、环境监测和化学加工。在有效信息技术的支持下，GCxGC的力量将使人们能够更好地了解化学成分和过程，这是未来科学进步和发现的基础。与公共卫生的相关性。今天，一些先进的实验室正在开创GCxGC的先河，用于各种应用，如空气、土壤、食物和水中暴露曲线的环境监测；血液、尿液、牛奶和呼吸样本中有毒产品的鉴定和定量；以及定性和定量代谢组学，以提供有机体生化状态或生化表型的整体视图。这些应用中的许多分析需要对样品进行详细的化学比较，例如，监测变化、与参考标准的比较、化学匹配或“指纹”，以及分类。GCxGC是一种用于这种比较分析的强大的新技术。这项提议将提供创新的信息技术，以支持这些应用程序的用户。