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NRT-URoL: Synthesizing Biology Across Scales – A Convergent Synthetic Biology Training Program

NRT-URoL: Synthesizing Biology Across Scales – A Convergent Synthetic Biology Training Program
NRT-URoL:跨尺度合成生物学 — 融合合成生物学培训计划
批准号:
2021900
负责人:
Julius Lucks
金额:
$299.5万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-09-01 至 2025-08-31

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中文摘要
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英文摘要
Synthetic biology is an emerging discipline that is generating innovations for synthesizing fuels, foods, and materials from sustainable sources, for building smart medicines to cure diseases, and for enabling global environmental stewardship. Thus, there is great potential for synthetic biology to touch almost every aspect of our daily lives. Given the promise of synthetic biology to benefit society, there is growing need to better understand the rules of life by which we may engineer biology, and to develop a diverse, synthetic biology-trained, entrepreneurial workforce. Today, synthetic biology concepts are primarily taught within traditional disciplinary boundaries, creating barriers to synergizing concepts across disciplines that could result in deeper understanding of biology and increased breakthrough innovations for society. This National Science Foundation Research Traineeship (NRT) award to the Center for Synthetic Biology at Northwestern University will break down these barriers by training graduate students using a new model for synthetic biology training, which specifically bridges disciplinary boundaries. This project anticipates training one hundred forty five (145) PhD students, including seventeen (17) funded trainees, from applied mathematics, biology, biomedical engineering, chemical engineering, civil and environmental engineering, and medicine degree programs.The guiding concepts of this training program are focused on Understanding the Rules of Life (URoL) through a synthetic approach: students will learn the principles of living systems across length and time scales—from molecules, to cells, to organisms, to communities—and then demonstrate this understanding through thesis research spanning the interfaces between these scales. This training program is inherently convergent. By integrating concepts across disciplines (e.g., biology, engineering, mathematics, data science), the program will help develop a core curriculum for synthetic biology training. The training plan consists of: (i) curricular development that introduces core biological principles along scales; (ii) skills workshops that give students core competencies in communication, computer programming, and experimental design; (iii) an experiential project within education, entrepreneurship, and policy tracks that prepares students to translate their training to impact broader society; (iv) integration of ethical considerations throughout each component; and (v) co-mentored thesis research that prepares students to work at the interface of different biological scales. The primary objectives of the project are to create a core curriculum for synthetic biology training, train synthetic biologists to communicate scientific ideas to diverse societal stakeholders, grow the synthetic biology workforce, broaden participation of women, underrepresented minorities, and people with disabilities, and build infrastructure to sustain innovative synthetic biology ecosystem.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 or convergent 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(5)
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科研奖励(0)
会议论文
DOI: 10.1146/annurev-biophys-092222-020832
发表时间: 2023
期刊: Annual Review of Biophysics
影响因子: 12.4
作者: [Abrahamson, Charlotte H., Palmero, Brett J., Kennedy, Nolan W., Tullman-Ercek, Danielle]
通讯作者: Tullman-Ercek, Danielle
Teaching systematic, reproducible model development using synthetic biology.
教授使用合成生物学进行系统的、可重复的模型开发。
DOI: 10.18260/2-1-370.660-132665
发表时间: 2023
期刊: Chemical engineering education
影响因子: --
作者: [Dray,KateE, Dreyer,KathleenS, Lucks,JuliusB, Leonard,JoshuaN]
通讯作者: Leonard,JoshuaN
Transitions: Evolving our Understanding of Dynamic RNA Folding and Function
  • 批准号:
    2310382
  • 项目类别:
    Standard Grant
  • 资助金额:
    $75.0万
  • 财政年份:
    2023
  • 负责人:
    Julius Lucks
  • 依托单位:
URoL:ASC: The design, development, and societal impact of rapid, in-home, water quality biosensors
  • 批准号:
    2319427
  • 项目类别:
    Standard Grant
  • 资助金额:
    $300.0万
  • 财政年份:
    2023
  • 负责人:
    Julius Lucks
  • 依托单位:
RAPID: Point-of-Need Detection of COVID-19 using CRISPR-Enabled Cell-Free Synthetic Biology
  • 批准号:
    2028651
  • 项目类别:
    Standard Grant
  • 资助金额:
    $20.0万
  • 财政年份:
    2020
  • 负责人:
    Julius Lucks
  • 依托单位:
RAPID: Collaborative Research: A cell-free synthetic biology platform for water quality monitoring - field testing and validation at the Camp Fire site in Paradise, California
  • 批准号:
    1929912
  • 项目类别:
    Standard Grant
  • 资助金额:
    $18.0万
  • 财政年份:
    2019
  • 负责人:
    Julius Lucks
  • 依托单位:
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