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NRT-HDR: Intersecting computational and data science to address grand challenges in plant biology

NRT-HDR: Intersecting computational and data science to address grand challenges in plant biology
NRT-HDR:交叉计算和数据科学以应对植物生物学的巨大挑战
批准号:
1828149
负责人:
Shin-Han Shiu
金额:
$300.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-09-01 至 2024-08-31

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中文摘要
翻译
植物对地球上的生命是不可或缺的,它们提供食物、能量和氧气,也是许多人造产品的基础。更好地了解植物科学将导致更安全的植物资源,鉴于全球人口的迅速增长,这一点更为重要。基因组学研究极大地提高了我们对植物功能的理解,基因组学的应用产生的数据集可能会彻底改变植物科学,并导致安全、可靠和可持续的食品和生物燃料生产。为了实现这些成果,迫切需要既了解植物生物学又具有计算技能的科学家。这项授予密歇根州立大学的国家科学基金会研究培训(NRT)奖将通过培养能够运用先进的计算和数据科学方法来解决植物生物学重大挑战的博士生来解决这一需求。该项目预计将培养大约70名博士生,其中包括38名来自植物生物学和计算数据科学项目的资助学员。学员将参与研究和课程作业,强调利用计算方法解决植物生物学中的“重大挑战”问题。培训将超越植物生物学中传统的基因组学和生物信息学方法,包括处理从分子到生态系统水平日益异构的多尺度数据所需的计算和建模方面的高级培训。这种类型的培训将允许学生解决复杂的问题,例如调查整个植物生命树的基因型-表型关系或高维植物数据的机器学习。此外,实习还包括专业发展机会、拓展活动和行业/政府实习,这些都有助于拓宽学员的职业选择,同时提高他们与广泛受众沟通的能力。培训结束后,学员将对植物和计算科学有一个核心的理解,在跨学科的生物和计算研究方面表现出色,并具备有效的沟通、领导、管理、教学和指导技能。受训人员将由植物科学和计算/数据科学方面的专家共同指导。为了实现培训目标,学员将参加一个包括以下内容的项目:(1)课程和研究活动,将培养一批具有计算科学和植物生物学双重专业知识的学员;(2)鼓励科学互动的双周论坛;(3)由学员领导的年度研讨会,吸引更广泛的科学受众,培养组织和领导技能;(4)工业和政府机构的实习机会;(5)为个人职业目标量身定制的专业发展活动,包括创业;(6)通过外展活动的公众参与,进一步增强学员与广泛受众沟通的能力。美国国家科学基金会研究实习生(NRT)计划旨在鼓励开发和实施大胆的、具有潜在变革性的STEM研究生教育培训新模式。该项目致力于通过创新、循证、适应不断变化的劳动力和研究需求的综合培训模式,在高优先级跨学科研究领域对STEM研究生进行有效培训。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
Plants are indispensable for life on earth, providing food, energy, and oxygen, as well as the basis for many man-made products. A better understanding of plant science will lead to more secure plant resources, which is even more important given the rapidly increasing global population. Genomics research has significantly advanced our understanding about how plants function, with the application of genomics yielding datasets that could revolutionize plant science and lead to safe, reliable, and sustainable production of food and biofuels. To achieve these outcomes, there is a critical need for scientists with both an understanding of plant biology and computational skills. This National Science Foundation Research Traineeship (NRT) award to Michigan State University will address this demand by training doctoral students who can employ advanced computational and data science approaches to address grand challenges in plant biology. The project anticipates training approximately seventy (70) PhD students, including thirty-eight (38) funded trainees from plant biology and computational data science programs. Trainees will engage in research and coursework that emphasize tackling "grand challenge" questions in plant biology by leveraging computational approaches. Training will go beyond the traditional genomics and bioinformatics approaches in plant biology to include the advanced training in computation and modeling required to handle increasingly heterogeneous, multi-scale data from the molecular to ecosystem levels. This type of training will allow students to tackle complex questions such as investigating genotype-phenotype relationships across the Plant Tree of Life or machine learning for high-dimensional plant data. In addition, the traineeship features professional development opportunities, outreach activities, and industry/governmental internships that serve to broaden trainees' career options while also improving their ability to communicate with a wide range of audiences. Upon completion of the training program, trainees will have a core understanding of plant and computational sciences, excel in interdisciplinary biological and computational research, and possess effective communication, leadership, management, teaching, and mentoring skills. Trainees will be co-advised by experts in plant science and computational/data science. To accomplish the training goals, trainees will participate in a program consisting of: (1) curricular and research activities that will create a cohort of trainees with dual expertise in computational sciences and plant biology, (2) a biweekly forum to encourage scientific interactions, (3) a trainee-led annual symposium that engages a wider scientific audience and builds organizational and leadership skills, (4) internship opportunities in industry and government agencies, (5) professional development activities tailored to individual career goals, including entrepreneurship, and (6) public engagement through outreach activities, further bolstering the ability of trainees to communicate with a wide range of audiences. The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.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.
期刊论文(21)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1002/tpg2.20328
发表时间: 2023-04
期刊: The Plant Genome
影响因子: --
作者: [P. Izquierdo;J. Kelly;S. Beebe;K. Cichy]
通讯作者: P. Izquierdo;J. Kelly;S. Beebe;K. Cichy
DOI: 10.1016/j.plantsci.2019.110335
发表时间: 2020-02-01
期刊: PLANT SCIENCE
影响因子: 5.2
作者: [Jiang, Nan, Lee, Yun Sun, Grotewold, Erich]
通讯作者: Grotewold, Erich
DOI: 10.1016/j.plantsci.2019.110364
发表时间: 2020-02-01
期刊: PLANT SCIENCE
影响因子: 5.2
作者: [Gomez-Cano, Lina, Gomez-Cano, Fabio, Gray, John]
通讯作者: Gray, John
DOI: 10.1016/j.molp.2022.01.003
发表时间: 2022-03-07
期刊: MOLECULAR PLANT
影响因子: 27.5
作者: [Hoopes, Genevieve, Meng, Xiaoxi, Finkers, Richard]
通讯作者: Finkers, Richard
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