"UAB Metabolomics Workshop: from design to decision"

描述（由申请人提供）：这是一个为期4天的代谢组学研讨会的开发和演示申请。虽然代谢组学的各个方面的框架将提交给与会者，研讨会的最终目标是准备研究人员推进代谢组学在转化研究中的使用，并指导高度跨学科的团队或代谢组学研究的合作。为此，讲习班将特别侧重于开发实验设计，以便有意义地执行代谢组学研究。结合这一重点，讲习班将提供一个有组织的，在代谢组学的实践经验。其目标是确保在这一轮的组学发展，与会者将学习从过去15年的组学研究中获得的经验。在第一年，在强有力的机构支持下，讲习班将处于发展阶段，最多限于16名参加者。这是为了仔细测试将构成近50%的研讨会活动的实践经验，然后将其扩展到将在第2-5年参加整个研讨会的40名与会者。我们将使用第一门课程的演讲者和与会者提供的反馈/建议来完善课程的各个方面-并在每年继续使用反馈意见和对前与会者如何使用代谢组学的评估来指导我们确定后续研讨会的内容和形式。讲习班将包括五个主要教学部分：（1）了解什么是代谢组学/代谢组学以及如何设计代谢组学实验;（2）收集和储存样品的关键问题;（3）选择代谢组学分析工具的基本原理，质谱（MS）和核磁共振（NMR）;（4）收集的代谢组学数据的处理和高维数据的统计分析;和（5）代谢组学的生物信息学、软件和计算机资源需求。与会者将通过实践经验介绍其中的每一个-他们将处理样品进行MS和NMR分析，与会者将获得从理想/优化到特定损坏数据的分析协议。这些方案的设计将显示设计不良的后果。所有的样本都将被处理，以便与会者可以应用他们在教学会议上学到的分析，统计和生物信息学方法。在最后一次会议上，与会者和研讨会教师将讨论已获得的数据。将有多达10个学生/博士后奖学金，将通过竞争过程中颁发的研讨会在第2-5年。这些费用将包括登记费、旅馆/伙食费和参加讲习班的旅费。分级注册费将适用于其他学生/博士后，教师和非大学与会者。 重点将放在确保两性平等和征聘服务不足的少数族裔。UAB是这个研讨会的绝佳环境，因为它在代谢组学所需的技术，其生物统计研究人员的力量和生物信息学的投资的优秀投资。

DESCRIPTION (provided by applicant): This is an application for the development and presentation of a 4-day Workshop on metabolomics. While the framework of all aspects of metabolomics will be presented to the attendees, the ultimate goal of the Workshop is to prepare investigators to advance the use of metabolomics in translational research and to direct highly interdisciplinary teams or collaborations in metabolomic studies. To that end, the Workshop will have a specific focus on development of experimental designs that will allow for the meaningful execution of metabolomics research. In combination with this emphasis, the Workshop will provide an organized, hands-on experience in metabolomics. The goal is to ensure in this round of -omics development, that attendees will learn from experiences gained from the last 15 years of -omics research. In the first year, with strong institutional support, th Workshop will be in a developmental phase and will be restricted to up to 16 participants. This is to carefully test the hands-on experience that will constitute nearly 50% of the Workshop activities before it is expanded to the 40 attendees who will attend the full Workshop in years 2-5. We will use feedback/advice given by the speakers and attendees of the first course to refine all aspects of the course - and continue throughout each year to use both feedback comments and assessment of how former attendees are using metabolomics to guide us in determining the content and shape of subsequent Workshops. The Workshop will consist of five main didactic sections: (1) understanding what metabolomics/metabonomics is and how to design a metabolomics experiment; (2) critical issues in collection and storage of samples; (3) rationales for choosing the analytical tools of metabolomics, mass spectrometry (MS) and nuclear magnetic resonance (NMR); (4) processing of collected metabolomics data and statistical analysis of high dimensional data; and (5) bioinformatics, software and computer resource needs for metabolomics. Attendees will be introduced to each of these through a hands-on experience - they will process samples for both MS and NMR analysis where attendees will be given analysis protocols that range from ideal/optimized to specifically corrupted data. These protocols will be designed to show the consequence of poor design. All samples will be processed so that the attendees can apply the analytical, statistical and bioinformatic methods they've been taught in the didactic sessions. In the last session, attendees and the Workshop faculty will discuss the data that has been obtained. There will be up to 10 student/postdoc fellowships that will be awarded through a competitive process for Workshops in year 2-5. These will consist of the registration, hotel/food costs and travel to the Workshop. Graded registration fees will apply to the other students/postdocs, faculty and non- university attendees. Emphasis will be placed ensuring gender equality and underserved minority recruitment. UAB is a superb environment for this Workshop because of its excellent investment in the technologies needed for metabolomics, the strength of its biostatistic research faculty and its investment in bioinformatics.