CDI-Type II: Collaborative Research: Computing with Biomolecules: From Network Motifs to Complex and Adaptive Systems

CDI-Type II：协作研究：生物分子计算：从网络基序到复杂自适应系统

• 批准号: 1028120
• 负责人: Christof Teuscher
• 金额: $ 30万
• 依托单位: Portland State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-10-01 至 2015-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1028120&HistoricalAwards=false
• 关键词: CDI; Type; II; Collaborative; Research

Can molecules be organized, or even self-organize, to perform complex tasks? This question seemingly should have an answer in the affirmative, because all the world around us, and especially the living things in it, is a mass of molecules. Yet the complexity of molecular systems, or networks, that chemistry has achieved to date pales in comparison with electronics and computers. A team of chemists, engineers, and computer scientists join forces to explore how molecules can be harnessed to achieve complex behaviors, including simple forms of computation, adaptation, and learning. They will work to discover the engineering principles needed to make large and useful molecular circuits. They will start by building networks of DNA enzymes, where actions of one enzyme stimulate another, just as protein enzymes stimulate one another in a living cell. They will build networks that can detect patterns of change in the environment; for example, the strength and the frequency of a periodic stimulation. Ultimately, they will build large networks that embody the ability to learn (memorize and generalize) patterns of past stimulation, and respond to new conditions in the environment accordingly.Intellectual Merit: The project will develop biocompatible, DNA molecular sensors and actuators that will be of immediate use in pathogen detection, non-invasive diagnostics, and intelligent therapeutics. As the project progresses, these will be combined with ever more capable biomolecular learning machines we will develop, but they can also be used independently by other researchers or medical doctors.Broader Impacts: The project will reach out to underserved communities in Oregon, New Mexico, and inner-city New York, providing high-school students and undergraduates an opportunity to engage in interdisciplinary scientific research.

分子能被组织起来，甚至自组织起来，来执行复杂的任务吗？这个问题似乎应该有一个肯定的答案，因为我们周围的所有世界，特别是其中的生物，都是分子的质量。然而，与电子学和计算机相比，迄今为止化学所实现的分子系统或网络的复杂性相形见绌。一个由化学家、工程师和计算机科学家组成的团队联手探索如何利用分子来实现复杂的行为，包括简单形式的计算、适应和学习。他们将致力于发现制造大型有用分子电路所需的工程原理。他们将首先建立DNA酶网络，其中一种酶的作用刺激另一种酶，就像蛋白质酶在活细胞中相互刺激一样。他们将建立能够检测环境变化模式的网络；例如，周期性刺激的强度和频率。最终，他们将建立大型网络，体现学习(记忆和概括)过去刺激模式的能力，并相应地对环境中的新情况做出反应。智力优势：该项目将开发生物兼容的DNA分子传感器和执行器，这些传感器和执行器将立即用于病原体检测、非侵入性诊断和智能治疗。随着项目的进展，这些将与我们将开发的更强大的生物分子学习机结合在一起，但它们也可以被其他研究人员或医学博士独立使用。广泛的影响：该项目将接触到俄勒冈州、新墨西哥州和纽约市中心服务不足的社区，为高中生和本科生提供从事跨学科科学研究的机会。