Robust, automated data tools for multidimensional separations in exposure assessment.

气相色谱（GC）和最近全面的二维气相色谱（GCxGC）是支持无数科学查询的技术。这些工具一般适用于混合物中小有机分子（<30-40个碳）的分离、定量和鉴定。在GCxGC的情况下，我们通常执行分离混合物包含2000-8000种不同的化合物。这些分析工具对于石油、环境污染物、法医科学和健康研究的分析至关重要。事实上，在上世纪五六十年代，正是气相色谱技术（无论好坏）推动了整个人工香料行业的蓬勃发展。研究计划的总体目标包括开发数据处理工具，以提高我们解释化学数据的能力，特别是GC和GCxGC分离产生的数据，并将这些工具提供给社区。作为加拿大国家代谢组学平台代谢组学创新中心的一个节点，我们通过服务运营为加拿大和国际研究社区提供专业知识和GCxGC-MS仪器。本科生、研究生甚至高中生都将在这个高度协作的多学科项目中学习，获得分析化学、计算机编程、项目管理、设计多学科研究项目和交流科学成果等宝贵技能。具体项目包括为我们的自动化工具开发一个在线门户网站，用于识别高度复杂的化学数据中的重要特征，并开发一个强大的自动化平台，用于处理来自数百或数千个样本的GCxGC研究数据集。其他学生将继续开发我们的色谱保留时间的基准设定热力学模型，提高我们在复杂样品中识别未知化合物的能力，例如含有新出现的污染物的环境样品。这些新的数据工具需要数据来进行测试。我们将在几个领域进行试点研究，以开发算法测试的数据集，这些数据集也有一些有意义的目的，并将作为未来研究项目的基础。试点研究包括分析生物液体（尿液、血液等）的新方法，以支持未来的健康诊断；燃烧/汽化方法与主流大麻烟雾成分之间关系的研究；开发非目标环境分析工具，对孤立的油气井周围的污染进行调查，并对可能影响原住民和马姆萨迪斯土地上土壤和水的遗留污染物进行调查。

Gas chromatography (GC), and more recently comprehensive two-dimensional gas chromatography (GCxGC) are technologies that support a myriad of scientific inquiries. These tools are generally applicable to the separation, quantification, and identification of small organic molecules (<30-40 carbons) in a mixture. In the case of GCxGC, we routinely perform separations of mixtures comprising 2000-8000 different compounds. These analytical tools are critical for the analysis of petroleum, environmental contaminants, forensic science, and health research. Indeed GC was the technology that allowed (for better or for worse) the proliferation of the entire artificial flavouring industry in the 1950s and 60s. Overarching goals for the research program include the development of data handling tools to improve our ability to interpret chemical data, in particular that arising from GC and GCxGC separations and to provide these tools to the community. As a node in The Metabolomics Innovation Centre, Canada's national metabolomics platform, we provide access to expertise and GCxGC-MS instrumentation to the Canadian and international research communities through our service operations. Undergrad, grad, and even high school students are integrated throughout the highly collaborative, multidisciplinary program, gaining valuable skills in analytical chemistry, computer programming, project management, designing multidisciplinary research projects, and communicating scientific results. Specific projects include the development of an online portal for our automated tools that identify important features in highly complex chemical data and developing a robust, automated platform for handling data sets from GCxGC studies with hundreds or thousands of samples. Other students will continue to develop our benchmark-setting thermodynamic models of chromatographic retention time, improving our ability to identify unknown compounds in complex samples such as environmental samples containing emerging contaminants of concern. These new data tools require data to test them. We will perform pilot studies in several areas to develop sets of data for algorithm testing that also have some meaningful purpose, and which will serve as the foundation for future research projects. Pilot studies include new approaches to the analysis of biofluids (urine, blood, etc) to support future health diagnostics; studies of the relationship between methods of combustion/vaporization and the composition of mainstream cannabis smoke; and development of non-target environmental analysis tools by performing surveys of contamination around orphaned oil and gas wells and legacy pollutants potentially affecting soil and water on First Nations and Métis lands.