HCC: Large: Collaborative Research: DNA Machine Builder: Creative molecular-machine design through mass-scale crowdsourcing
HCC:大型:协作研究:DNA Machine Builder:通过大规模众包进行创意分子机器设计
基本信息
- 批准号:1212940
- 负责人:
- 金额:$ 190.92万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2012
- 资助国家:美国
- 起止时间:2012-09-01 至 2016-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This project will develop and evaluate methods by which large numbers of humans, together with computers, can advance the field of synthetic biology by assembling a corpus of creative designs of molecular machines built from DNA segments as well as other molecular structures. Specifically, it will develop a massively-distributed DNA machine construction game that will enable human worldwide collective creativity to be applied to problems ranging from the design of novel self-organizing materials to smart therapeutics that can sense and respond to their environment. The innovative approach is to cast problems of constructing molecular nano-machines with specific functions as a collaborative machine design game governed by the rules of DNA strand interactions. This approach points to a new paradigm for future science, in which a large group of people together with computers work on difficult creative problems, finding solutions that could not be found by computers alone, or by people alone, or without the massive participation of users. If successful, this approach could change science profoundly, with wide-ranging impact on many disciplines including nanotechnology, biochemistry, medicine, and even social and economic behavior analysis. Although the project specifically focuses on games that use DNA strands as principal building blocks of nano-machines, the potential set of applications is large, and encompasses three of the most significant problems facing humanity today. The primary goal of the computer game is to develop and focus collective creativity towards a design space of machines governed by DNA molecular mechanisms. It is currently not known whether this form of sophisticated scientific design creativity can be developed rapidly with non-experts. It is also unknown whether this developed creativity can exceed the current capabilities of the scientific community. This project aims to answer a number of fundamental questions: How does one develop computer games to maximize targeted human design creativity? What are the guiding principles of successful molecular design games? How do we generalize game-development principles to the widest possible range of synthetic biology problems? How can we develop a collective creative design process that outperforms any individual creativity? How do we learn from the way people play the game, and distill their strategies towards stronger automated approaches? The successful outcomes of this project can have a wide ranging impact on health and medicine. One such problem is the design of diagnostic devices and imaging technologies. The game players will work to develop DNA sensors and circuits that can autonomously analyze and interpret the information encoded in a set of molecular disease markers. This approach will enable new devices for multi-analyte testing in low resource settings and will lead to novel medical imaging technologies. Another challenge is design of novel targeted therapeutics, in this case novel RNA-based therapeutics that can autonomously sense and analyze their environment and activate a therapeutic response only where required. A third problem is design of novel materials. This project will develop DNA nanostructures with the potential for the massively parallel self-assembly materials with desired electronic, optical, or chemical properties. These materials will find applications in areas from artificial photosynthesis to biofuels production. This effort will have positive broader impacts for informal science education. The game will reach out to people of all demographic profiles in hope of educating everyone about key molecular research challenges, empowering them to solve important scientific problems, and engaging them in research and science in general. Hopefully, the best scores in these games turn into seminal discoveries with deep impact on people's lives. Also, undergraduates will be involved directly in game development, and a course centered around prototyping of molecular games will be offered. Furthermore, the research team will work with education scientists to develop a new curriculum about DNA and how nature uses molecular mechanisms to achieve function. The curriculum will be anchored around the DNA Machine game and will be piloted in US high schools.
该项目将开发和评估大量人类与计算机一起通过组装由DNA片段以及其他分子结构构建的分子机器的创造性设计语料库来推进合成生物学领域的方法。 具体来说,它将开发一个分布式的DNA机器构建游戏,使人类的全球集体创造力能够应用于从新型自组织材料的设计到能够感知和响应环境的智能治疗等问题。创新的方法是铸造的问题,构建具有特定功能的分子纳米机器作为一个合作的机器设计游戏由DNA链相互作用的规则。 这种方法指出了未来科学的一种新范式,在这种范式中,一大群人与计算机一起研究困难的创造性问题,找到单靠计算机或人无法找到的解决方案,或者没有用户的大量参与。如果成功,这种方法可能会深刻地改变科学,对许多学科产生广泛的影响,包括纳米技术,生物化学,医学,甚至社会和经济行为分析。虽然该项目特别关注使用DNA链作为纳米机器主要构建模块的游戏,但潜在的应用范围很大,包括当今人类面临的三个最重要的问题。 电脑游戏的主要目标是开发和集中集体创造力,以设计由DNA分子机制控制的机器空间。目前还不知道这种复杂的科学设计创造力是否能在非专家的情况下迅速发展。也不知道这种发达的创造力是否能超过科学界目前的能力。该项目旨在回答一些基本问题:如何开发计算机游戏,以最大限度地提高有针对性的人类设计创造力?成功的分子设计游戏的指导原则是什么?我们如何将游戏开发原则推广到尽可能广泛的合成生物学问题?我们如何才能开发出一个集体的创造性设计过程,超越任何个人的创造力?我们如何从人们玩游戏的方式中学习,并将他们的策略提炼为更强大的自动化方法? 该项目的成功成果可以对健康和医学产生广泛的影响。 其中一个问题是诊断设备和成像技术的设计。游戏玩家将致力于开发DNA传感器和电路,这些传感器和电路可以自主分析和解释编码在一组分子疾病标记中的信息。这种方法将使新设备能够在低资源环境中进行多分析物测试,并将导致新的医学成像技术。另一个挑战是设计新的靶向治疗剂,在这种情况下,新的基于RNA的治疗剂可以自主感知和分析其环境,并仅在需要时激活治疗反应。第三个问题是新材料的设计。该项目将开发具有大规模并行自组装材料潜力的DNA纳米结构,并具有所需的电子,光学或化学性质。这些材料将在从人工光合作用到生物燃料生产的领域中找到应用。 这一努力将对非正规科学教育产生更广泛的积极影响。 该游戏将接触所有人口统计学特征的人,希望教育每个人了解关键的分子研究挑战,使他们能够解决重要的科学问题,并使他们参与研究和科学。希望这些游戏中的最好成绩能成为对人们生活产生深远影响的开创性发现。此外,本科生将直接参与游戏开发,并将提供一个以分子游戏原型为中心的课程。此外,研究小组将与教育科学家合作,开发一门关于DNA以及大自然如何利用分子机制实现功能的新课程。该课程将围绕DNA Machine游戏进行,并将在美国高中进行试点。
项目成果
期刊论文数量(0)
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Zoran Popovic其他文献
Brain points: a growth mindset incentive structure boosts persistence in an educational game
大脑要点:成长型思维激励结构可提高教育游戏的持久性
- DOI:
- 发表时间:
2014 - 期刊:
- 影响因子:0
- 作者:
Eleanor O'Rourke;K. Haimovitz;Christy Ballweber;C. Dweck;Zoran Popovic - 通讯作者:
Zoran Popovic
Percutaneous transarterial balloon dilatation of the mitral valve: five year experience.
经皮经动脉二尖瓣球囊扩张术:五年经验。
- DOI:
10.1136/hrt.67.2.185 - 发表时间:
1992 - 期刊:
- 影响因子:0
- 作者:
U. Babic;S. Grujicic;Zoran Popovic;Z. Djurisic;P. Pejcic;Mihailo Vučinić - 通讯作者:
Mihailo Vučinić
Proactive Sensing for Improving Hand Pose Estimation
用于改进手部姿势估计的主动传感
- DOI:
10.1145/2858036.2858587 - 发表时间:
2016 - 期刊:
- 影响因子:0
- 作者:
Dun;Min Sun;Christy Ballweber;Seth Cooper;Zoran Popovic - 通讯作者:
Zoran Popovic
Generalizing locomotion style to new animals with inverse optimal regression
通过逆最优回归将运动方式推广到新动物
- DOI:
- 发表时间:
2014 - 期刊:
- 影响因子:6.2
- 作者:
K. Wampler;Zoran Popovic;J. Popović - 通讯作者:
J. Popović
PROGNOSTIC VALUE OF ECHO-DOPPLER GUIDED AV DELAY OPTIMIZATION FOLLOWING CARDIAC RESYNCHRONIZATION THERAPY
- DOI:
10.1016/s0735-1097(16)31492-9 - 发表时间:
2016-04-05 - 期刊:
- 影响因子:
- 作者:
Srikanth Koneru;Zoran Popovic;Paul Cremer;Patrick Tchou;Bruce Wilkoff;Bruce Lindsay;Brian Griffin;Richard Grimm - 通讯作者:
Richard Grimm
Zoran Popovic的其他文献
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{{ truncateString('Zoran Popovic', 18)}}的其他基金
Investigating the Effects of Computational Thinking Games on Mathematical and Scientific Practices
研究计算思维游戏对数学和科学实践的影响
- 批准号:
1639576 - 财政年份:2016
- 资助金额:
$ 190.92万 - 项目类别:
Standard Grant
CI-EN: Collaborative Research: Enhancement of Foldit, a Community Infrastructure Supporting Research on Knowledge Discovery Via Crowdsourcing in Computational Biology
CI-EN:协作研究:Foldit 的增强,Foldit 是一个支持计算生物学中通过众包进行知识发现研究的社区基础设施
- 批准号:
1625811 - 财政年份:2016
- 资助金额:
$ 190.92万 - 项目类别:
Standard Grant
BIGDATA: F: BCC: Data driven optimization of classroom learning activities
BIGDATA:F:BCC:数据驱动的课堂学习活动优化
- 批准号:
1546510 - 财政年份:2015
- 资助金额:
$ 190.92万 - 项目类别:
Standard Grant
Eager: Large Scale Neuron Reconstruction through Development of Crowdsourced Reconstruction Experts
Eager:通过众包重建专家的发展进行大规模神经元重建
- 批准号:
1551063 - 财政年份:2015
- 资助金额:
$ 190.92万 - 项目类别:
Standard Grant
HCC-Small: Protein Design Through Massively Distributed Video Games
HCC-Small:通过大规模分布式视频游戏进行蛋白质设计
- 批准号:
0811902 - 财政年份:2008
- 资助金额:
$ 190.92万 - 项目类别:
Standard Grant
CAREER: Reusable, Realistic Motion Libraries for Computer Animation
职业:可重复使用的、逼真的计算机动画运动库
- 批准号:
0092970 - 财政年份:2001
- 资助金额:
$ 190.92万 - 项目类别:
Continuing Grant
Surface and Motion Capture for High Fidelity Synthesis of Digital Humans
用于数字人高保真合成的表面和运动捕捉
- 批准号:
0098005 - 财政年份:2001
- 资助金额:
$ 190.92万 - 项目类别:
Continuing Grant
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