Comparative Visualization and Analysis for GCxGC

GCxGC 的比较可视化和分析

• 批准号: 6834079
• 负责人: STEPHEN E REICHENBACH
• 金额: $ 9.95万
• 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 2005-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6834079
• 关键词: computer program /software; computer system design /evaluation; gas chromatography; imaging /visualization /scanning; informatics; visual fields

DESCRIPTION (provided by applicant): This project will investigate and develop methods for computer-based comparative visualization and interactive analysis of complex data generated by comprehensive two-dimensional gas chromatography (GCxGC). GCxGC is an emerging technology that provides an order-of-magnitude increase in separation capacity over traditional GC. Today, a few advanced laboratories around the world are pioneering GCxGC for a variety of applications such as environmental analyses of exposure profiles in air, soil, food, and water, and health-care analyses for the identification and quantification of toxic products in blood, urine, milk, and breath samples. Many analyses in these applications require detailed chemical comparisons of samples, e.g., the comparison of a new sample with a previous sample to detect and monitor changes or the comparison of a test sample with a reference sample to identify and quantify differences in chemical composition. GCxGC is a powerful technology for comparative analyses. The principal challenge for GCxGC 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 methods and tools for comparative visualization and interactive analysis of GCxGC data. Visualizations for comparative analyses of GCxGC scalar fields will be developed using a Multi-View Multi-Layer (MVML) framework in a Model-View-Controller (MVC) architecture. Within the MVML framework, several different strategies for visualization will be developed, utilizing colorization and animation. The expected results will provide a foundation for development of a computer-based system for comparative GCxGC analyses of complex samples and will advance knowledge of frameworks and methods for visualization and interactive analysis of GCxGC data and other two-dimensional scalar fields.

描述（由申请人提供）：该项目将研究和开发基于计算机的比较可视化和对综合二维气相色谱（GCxGC）生成的复杂数据进行交互式分析的方法。 GCxGC 是一项新兴技术，与传统 GC 相比，分离能力提高了一个数量级。如今，世界各地的一些先进实验室正在率先将 GCxGC 用于各种应用，例如空气、土壤、食物和水中暴露曲线的环境分析，以及用于识别和定量血液、尿液、牛奶和呼吸样本中有毒产物的医疗保健分析。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，将新样品与先前样品进行比较以检测和监测变化，或者将测试样品与参考样品进行比较以识别和量化化学成分的差异。 GCxGC 是一种强大的比较分析技术。 GCxGC 面临的主要挑战是难以分析和解释其生成的大量复杂数据。 GCxGC 数据的数量和复杂性需要研究和开发新的信息技术。该项目将开发和演示用于 GCxGC 数据比较可视化和交互式分析的方法和工具。用于 GCxGC 标量场比较分析的可视化将使用模型-视图-控制器 (MVC) 架构中的多视图多层 (MVML) 框架进行开发。在 MVML 框架内，将利用着色和动画开发几种不同的可视化策略。预期结果将为开发用于复杂样品的比较 GCxGC 分析的计算机系统奠定基础，并将增进对 GCxGC 数据和其他二维标量场的可视化和交互式分析的框架和方法的了解。