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.

分子可以组织甚至是自组织以执行复杂的任务吗？这个问题似乎应该在肯定中有一个答案，因为我们周围的整个世界，尤其是其中的生物都是一堆分子。然而，与电子和计算机相比，化学的分子系统或网络的复杂性已达到苍白。一个化学家，工程师和计算机科学家团队联手探索如何利用分子来实现复杂的行为，包括简单的计算，适应和学习。他们将努力发现制造大型和有用的分子电路所需的工程原理。它们将从建立DNA酶的网络开始，其中一种酶的作用会刺激另一种酶，就像蛋白质酶在活细胞中互相刺激一样。他们将建立可以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，以体现过去刺激的学习（记忆和推广）模式，并相应地应对环境中的新状况。智能优点：该项目将发展生物相容性的DNA分子传感器和执行器，这些传感器和执行器将立即在病原体检测，非影响力诊断诊断和智能方面和智能的诊断和智能中使用。 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.