EAGER: Algorithmic aspects of molecular circuits and molecular machines

EAGER：分子电路和分子机器的算法方面

• 批准号: 0947670
• 负责人: Ashish Goel
• 金额: $ 20万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2011-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0947670&HistoricalAwards=false
• 关键词: EAGER; Algorithmic; aspects; molecular; circuits

Project SummaryProposal #: 0947670PI: Ashish GoelWe are used to thinking of DNA as a biological molecule. However, DNA, its cousin the RNA, and other associated molecules such as enzymes, are also engineering building blocks. Think of them as ?combinatorial Legos? which fit together and inter-operate not just by mechanics and geometry but also using the chemical sequence imprinted on them. This has many revolutionary potential applications. This also poses many mathematical and algorithmic questions which are both interesting in their own right and also provide a framework to devise useful experimental techniques. The PI proposes to conduct research in the emerging field of ?molecular algorithms?, i.e., algorithms which are meant to be implemented on molecules. This study will proceed in two broad directions: molecular machines and molecular circuits. The two areas are linked both thematically and in terms of techniques. We will constantly consult with practitioners in this field, so that the results of this research are both novel and useful.Intellectual merit: Molecular algorithms require tools and techniques that are considerably different from traditional algorithms. We can not assume building blocks such as memories, actuators, sensors, transistors, processors etc; rather, these are often the things we are trying to devise using more basic primitives such as DNA hybridization, enzymatic reactions, and migration. Consequently, advances in molecular algorithms are likely to require novel mathematical techniques that will enrich the disciplines of coding theory, combinatorial algorithms, and probabilistic analysis.Broad impact: Molecular machines have been proposed as sensors, actuators, and drug delivery mechanisms. Molecular circuits have the potential to finely control other molecular processes. Much of the hard work in developing these ideas is being done by experimentalists. However, theoretical tools such as the one we propose to develop also have an important role to play in realizing the full potential of this area and in deciding upon the most promising experimental directions. In addition, molecular algorithms could facilitate sophisticated tasks such as counting, shape recognition, precisely controlled crystal growth etc. at nano-scales.The PI has developed a class in molecular algorithms which he will update and teach bi-annually. Also, many graduate students will receive valuable research experience in this important area.

项目摘要提案编号：0947670 PI：Ashish Goel我们习惯于将DNA视为生物分子。然而，DNA，它的表亲RNA，以及其他相关的分子，如酶，也是工程构建模块。把他们当成？组合乐高它们不仅通过机械和几何结构，而且还通过其上的化学序列结合在一起并相互作用。这有许多革命性的潜在应用。这也提出了许多数学和算法问题，这些问题本身就很有趣，也提供了一个框架来设计有用的实验技术。PI建议在新兴领域进行研究？分子算法？也就是说，这些算法应该在分子上实现。这项研究将在两个大方向进行：分子机器和分子电路。这两个领域在主题和技术方面都有联系。我们将不断地与这一领域的从业者进行磋商，使这项研究的结果既新颖又有用。智力价值：分子算法需要与传统算法有很大不同的工具和技术。我们不能假设构建模块，如存储器，执行器，传感器，晶体管，处理器等;相反，这些通常是我们试图使用更基本的原语，如DNA杂交，酶反应和迁移来设计的东西。因此，分子算法的进步可能需要新颖的数学技术，这将丰富编码理论、组合算法和概率分析等学科。广泛的影响：分子机器已被提议作为传感器、执行器和药物输送机制。分子电路具有精细控制其他分子过程的潜力。发展这些想法的大部分艰苦工作是由实验者完成的。然而，理论工具，如我们建议开发的一个也发挥了重要作用，在实现这一领域的全部潜力，并在决定最有前途的实验方向。此外，分子算法可以促进复杂的任务，如计数，形状识别，精确控制晶体生长等。在纳米尺度上。PI已经开发了一个分子算法的类，他将每半年更新和教授。此外，许多研究生将在这一重要领域获得宝贵的研究经验。