IRES Track II: Cross-disciplinary Computational Biology Training

计算生物学的跨学科科学已经转变为一门强大的学科，走出了其母学科--计算机科学和生物学--的阴影。目前，在学术和工业研发机构中，计算生物学是生物学、生物技术、医疗保健和公共卫生的重要组成部分。然而，专门劳动力的培训机会往往是有限的；计算生物学领域对许多大学来说是一个挑战，因为它们的系结构和学科孤岛。在快速发展的科学界，在科学从业者之间共享数据的做法正在开辟新的研究途径，例如使用多学科方法遏制流行病，或为未来的医疗保健开发精确医学。与此同时，生物数据的财富积累速度快于研究界分析它们的能力。分析的一个瓶颈是缺乏计算生物学家。为了填补美国研究生的一些培训空白，我们将提供两个高级研究院(ASI)，由来自不同计算生物学学科的国际专家组成。拟议的两个ASIS将培训学生，其中大多数将来自EPSCoR州，特别努力招募少数群体和妇女，关于计算生物学的各种基本/理论方面的培训，并使他们了解该领域的最新应用和发展。此外，为了让参与者有机会了解计算生物学的各种职业可能性，将邀请经验丰富的学术人员、核心服务提供商、具有相关行业经验的科学家以及从事知识产权工作的个人和初创公司担任这些ASIS的讲师。ASIS对学生参与者科学准备的影响与NSF促进科学进步的使命非常一致。在ASIS期间对参与者进行计算生物学不同方面的培训将有助于缓解瓶颈，并与NSF促进国民健康的使命很好地结合在一起。作为一名计算生物学家，成功的关键因素之一是多才多艺，并有能力使自己与该领域的不同需求保持一致。通常，学生只接受计算生物学的一个或几个方面的培训，这些方面与他们最近的研究有关。研究生很少以任何有意义的方式接触到组成计算生物学的广泛领域。拟议的两个ASIS不同于传统的ASIS，后者通常深入涵盖一个特定的主题。相反，拟议的ASIS将涵盖计算生物学的多个跨学科主题。学习是一个复杂的现象，最有效的培训方法是在讲课、促进讨论、互动和实际应用之间取得平衡。这些ASIS将通过实施包括讲座、实践活动和项目在内的教学方法，将上述学习工具的所有方面结合起来。这些研讨会将在国际环境中举行，这既提供了接触文化的机会，也提供了美国以外计算生物学领域的领导者的机会。随着非美国/欧洲科学和经济的重要性继续快速增长，特别是在计算生物学领域，亚洲的地理位置非常重要。拟议中的ASIS将在马来西亚佩尔达纳大学和新加坡国家超级计算中心(NSCC)主办，这两个中心是亚洲占主导地位的生物技术中心。参与者将有机会与来自亚洲、美国和欧洲的国际学生、教师和行业领袖建立专业关系。在讲习班期间，将鼓励学员参加文化体验，使他们接触东道国的历史和文化。将为ASI建立一个网站，用于招聘、协调和评估。将在同行评议的期刊上报告由参与者判断的活动及其对培训参与者的有效性的摘要。学生将主要从EPSCoR州中挑选，重点是从少数族裔(特别是美国原住民)和女性中招募，目的是增加未被充分代表的群体对计算生物学的参与。该项目由国际科学与工程办公室(OISE)和既定的激励竞争研究计划(EPSCoR)共同资助。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The cross-disciplinary science of computational biology has transformed into a robust subject of its own, emerging out of the shadows of its parent topics - computer science and biology. Currently, computational biology is an essential part of biology, biotechnology, health care and public health in both academic and industrial research and development institutions. However, training opportunities for the specialized workforce are often limited; the field of computational biology presents a challenge to many universities because of their departmental structures and disciplinary silos. In the rapidly evolving scientific world, the practice of sharing data among science practitioners is opening up new research avenues such as containing a pandemic using multidisciplinary approaches or the development of precision medicine for the future of health care. At the same time, the wealth of biological data is accumulating faster than the research community’s ability to analyze them. One bottleneck for analysis is a shortage of computational biologists. In order to fill some of the training gaps for U.S. graduate students, we will offer two Advanced Studies Institutes (ASI) with international experts from various disciplines of computational biology. The two proposed ASIs will train the students, the majority of whom will be from EPSCoR states with a special effort to recruit minorities and women, on diverse fundamental/theoretical aspects of computational biology as well as expose them to recent applications and developments in the field. In addition, to give the participants an opportunity to learn about various career possibilities in computational biology, an experienced team of academic faculties, core service providers, scientists with experience in relevant industries and individuals working on intellectual properties and start-up companies will be invited as instructors in these ASIs. The impact of the ASIs on scientific preparedness of student participants aligns well with NSF’s mission to promote the progress of science. Training the participants on different aspects of computational biology during the ASIs will contribute to the easing of the bottleneck and aligns well to NSF’s mission to advance the national health.One of the key factors to success as a computational biologist is versatility and the ability to align oneself with the diverse demands of the field. Typically, students are trained in only one or very few aspects of computational biology relevant to their immediate research. It is rare that graduate students are exposed, in any meaningful way, to the breadth of fields that compose computational biology. The two proposed ASIs are different from traditional ASIs, which typically cover one specific subject matter in depth. Instead, the proposed ASIs will cover multiple cross-disciplinary topics in computational biology. Learning is a complex phenomenon, and the most effective training approaches combine a balance between lectures, promotion of discussions, interactivity and practical applications. These ASIs will combine all aspects of the aforementioned learning tools by implementing instruction methods comprising of lectures, hands-on activities and projects. These workshops will be held in an international setting, which provides both exposure to culture and as well as leaders in computational biology outside of the USA. The locations in Asia are important as non-American/European science and economy continues to grow rapidly in importance, especially within computational biology. The proposed ASIs will be hosted at the University of Perdana in Malaysia and the National Supercomputing Center in Singapore (NSCC) - two dominant biotechnology hubs of Asia. The participants will have the opportunity to build professional relationships with international students, faculties and industry leaders from Asia, USA and Europe. During the workshop, participants will be encouraged to participate in cultural experiences that will expose them to the history and culture of the host country. A website will be built for the ASI and will be used for recruitment, coordination and evaluation. A summary of the activities and their effectiveness in training participants, as judged by the participants, will be reported in a peer reviewed journal. Students will be primarily selected from EPSCoR states, with emphasis on recruiting from minorities (especially Native American) and women, with the aim of increasing participation of under-represented groups in computational biology.This project is jointly funded by the Office of International Science and Engineering (OISE), and the Established Program to Stimulate Competitive Research (EPSCoR).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.