The Mathematical Sciences in Obesity Research

项目总结/摘要 数学科学包括工程学、统计学、计算机科学、物理学、计量经济学和 作为数学的数学越来越多地被应用于促进我们对原因的理解， 后果和减轻肥胖。这些应用程序超越了易于实现的常规方法 在可用的商业软件中。相反，它们越来越多地涉及计算要求高的任务， 开发新的分析方法和软件，新的衍生物，以及特殊程度的 两种或多种现有技术的交叉。此外，这些方法和应用继续 进步;今天的技术和问题与五年前的技术和问题不同， 更新课程是必不可少的。数学科学与肥胖研究的界面进展 需要对两个学科的调查人员进行双边培训。然而，据我们所知， 这是唯一一个为科学家提供此类培训的持续资源。我们成功的五天短期课程的特点 一些世界上最优秀的科学家在这个接口工作，以填补未满足的需求，提供多个，主题- 驱动模块，旨在弥合学科。我们提供的课程的需求和成功 在过去的五年里，每年有100多人报名参加我们的课程， 超过1300名用户访问了我们的课程视频档案，并导致了十几次合作 在成功的赠款申请或同行评议的出版物从我们的课程参与者和教师。第一 模块作为一个共同的方向，为调查人员接近界面主要是从一个 定量或肥胖透镜，其次是8个模块的主题，如使用能量建模体重变化 平衡，人群中的建模效应，肥胖症的基因组分析，对肥胖症的行为反应建模， 传感器和工程模型，比例定律和肥胖。讲座经过视频录制并发布到我们的 课程网站供免费浏览，从而扩大我们的课程覆盖面。因为个人在学习中 复杂的任务时，他们可以与材料互动，我们包括一些互动会议设计 让参与者参与主动学习。这些会议包括小组讨论，与观众的辩论 参与、问答和基于发现的学习活动。这些都是由 我们在上一个供资周期中所取得的进展，将成为最好的服务，并得到我们的参与者的高度赞赏。 高级教师提供讲座，并领导小组和个人咨询与参与者的主题，如 获得资助和跨学科的职业生涯。肥胖中的新数学科学 卓越研究（更多）奖将吸引课程之外的参与者，以确定一个杰出的 在接下来的几年里，肥胖定量研究的出版物将被授予荣誉。NIH和 科学界普遍表示需要在数学科学的界面上进行更多的培训 和关键的生物医学领域，我们要求有机会继续成为解决方案的一部分。

Project Summary/Abstract The mathematical sciences including engineering, statistics, computer science, physics, econometrics, and mathematics qua mathematics are increasingly being applied to advance our understanding of the causes, consequences, and alleviation of obesity. These applications go beyond routine approaches easily implemented in available commercial software. Rather, they increasingly involve computationally demanding tasks, development of novel analytic methods and software, new derivations, and an exceptional degree of interdigitation of two or more existing techniques. Moreover, these methods and applications continue to advance; the techniques and questions today are not identical to those from five years ago and continuing to refresh curricula is essential. Advances at the interface of the mathematical sciences and obesity research require bilateral training for investigators in both disciplines. Yet, our existing proven course is, to our knowledge, the only ongoing resource to provide such training by scientists. Our successful five day short course features some of the world’s finest scientists working at this interface to fill the unmet need by providing multiple, topic- driven modules designed to bridge the disciplines. The demand for and success of the course we offered annually for the last five years is evidenced by the facts that over 100 people have enrolled in our course, that over 1300 users have accessed our course video archives, and that over a dozen collaborations have resulted in successful grant applications or peer-reviewed publications from our course participants and faculty. The first module serves as a common orientation for investigators approaching the interface predominantly from a quantitative or obesity lens, followed by 8 modules with topics such as modeling weight change using energy balance, modeling effects in populations, genomic analysis in obesity, modeling behavioral responses to obesity, sensor and engineering models, and scaling laws and obesity. Lectures are video-recorded and posted to our course website for free viewing, thereby extending the reach of our course. Because individuals learn best in complex tasks when they can interact with the material, we include a number of interactive sessions designed to engage the participants in active learning. These sessions include panel discussion, debates with audience participation, question and answer periods, and discovery-based learning activities. These have been refined by us over the prior funding cycle to be those that best serve and are most highly appreciated by our participants. Senior faculty offer lectures and lead small group and individual consultations with participants on topics such as grant acquisition and navigating an interdisciplinary career. The new Mathematical sciences in Obesity Research Excellence (MORE) Prize will engage participants beyond the course to identify an outstanding publication on quantitative obesity research to be honored at the following years’ course. The NIH and the scientific community at large have voiced the need for more training at the interface of the mathematical sciences and key biomedical domains, and we request the opportunity to continue to be part of the solution.