Collaborative Research: Molecular Programming Architectures, Abstractions, Algorithms, and Applications
合作研究:分子编程架构、抽象、算法和应用
基本信息
- 批准号:1317694
- 负责人:
- 金额:$ 500万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2013
- 资助国家:美国
- 起止时间:2013-10-01 至 2019-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The computing revolution began over two thousand years ago with the advent of mechanical devices for calculating the motions of celestial bodies. Sophisticated clockwork automata were developed centuries later to control the machinery that drove the industrial revolution, culminating in Babbage's remarkable design for a programmable mechanical computer. With the electronic revolution of the last century, the speed and complexity of computers increased dramatically. Using embedded computers we now program the behavior of a vast array of electro-mechanical devices, from cell phones and satellites to industrial manufacturing robots and self-driving cars. The history of computing has taught researchers two things: first, that the principles of computing can be embodied in a wide variety of physical substrates from gears to transistors, and second, that the mastery of a new physical substrate for computing has the potential to transform technology. Another revolution is just beginning, one whose inspiration is the incredible chemistry and molecular machinery of life, one whose physical computing substrate consists of synthetic biomolecules and designed chemical reactions. Like the previous revolutions, this "molecular programming revolution" will have the principles of computer science at its core. By systematically programming the behaviors of a wide array of complex information-based molecular systems, from decision-making circuitry and molecular-scale manufacturing to biomedical diagnosis and smart therapeutics, it has the potential to radically transform material, chemical, biological, and medical industries. With molecular programming, chemistry will become a major new information technology of the 21st century.This Expeditions-in-Computing project aims to establish solid foundations for molecular programming. Building on advances in DNA nanotechnology, DNA computing, and synthetic biology, the project will develop methods for programmable self-assembly of DNA strands to create sophisticated 2D and 3D structures, dynamic biochemical circuitry based on programmable interactions between DNA, RNA, and proteins, and integrated behaviors within spatially organized molecular systems and living cells. These architectures will provide systematic building blocks for creating programmable molecular systems able to sense molecular input, compute decisions about those inputs, and act on their environment. To manage system complexity and to provide modularity, the project will establish abstraction hierarchies with associated high-level languages for programming structure and behavior, compilers that turn high-level code into lists of synthesizable DNA sequences, and analysis software that can predict the performance of the sequences. This will allow molecular programmers to specify, design, and verify the correctness of their systems before they are ever synthesized in the laboratory. In addition to these software tools, the project will study the theory of molecular algorithms in order to understand the potential and limitations of information-based molecular systems, what makes them efficient at the tasks they can perform, and how they can be effectively designed and analyzed. Putting the products of this fundamental research to the test, the project will pursue real-world applications such as molecular instruments for probing biological systems and programmable fabrication of nanoscale devices.This project will expand the network of scientists and engineers working in molecular programming by building a diverse community of students, teachers, researchers, scientists, and engineers. This community will be fostered through the creation of publicly accessible software tools, courses, textbooks, workshops, tutorials, undergraduate research competitions, and popular science videos to teach the principles and methods of molecular programming and to engage young researchers and the public in this exciting new field. Industrial partnerships with relevant biotechnology and other high-tech companies will ensure fast transfer of knowledge generated into real-world products. Perhaps most importantly, as molecular programming becomes a widespread technology, it has the potential to transform industry with new complex nanostructured materials, to transform chemistry with integrated and autonomous control of reactions, to transform biology with advanced molecular instruments, and to transform health care with more sophisticated diagnostics and therapeutics.
计算革命始于两千多年前,当时出现了计算天体运动的机械装置。几个世纪后,精密的发条自动机被开发出来,用于控制推动工业革命的机械,最终在巴贝奇的可编程机械计算机的卓越设计中达到顶峰。随着上个世纪的电子革命,计算机的速度和复杂性急剧增加。使用嵌入式计算机,我们现在可以对大量机电设备的行为进行编程,从手机和卫星到工业制造机器人和自动驾驶汽车。计算的历史教会了研究人员两件事:第一,计算的原理可以体现在从齿轮到晶体管的各种各样的物理基底中,第二,掌握一种新的计算物理基底有可能改变技术。 另一场革命才刚刚开始,它的灵感来自令人难以置信的化学和生命的分子机制,它的物理计算基底由合成生物分子和设计的化学反应组成。 像以前的革命一样,这场“分子编程革命”将以计算机科学的原理为核心。 通过系统地编程各种复杂的基于信息的分子系统的行为,从决策电路和分子规模的制造到生物医学诊断和智能治疗,它有可能从根本上改变材料,化学,生物和医疗行业。 随着分子程序设计的出现,化学将成为世纪重要的新信息技术。本计划旨在为分子程序设计奠定坚实的基础。 基于DNA纳米技术,DNA计算和合成生物学的进步,该项目将开发DNA链的可编程自组装方法,以创建复杂的2D和3D结构,基于DNA,RNA和蛋白质之间可编程相互作用的动态生化电路,以及空间组织分子系统和活细胞内的集成行为。这些架构将为创建可编程分子系统提供系统构建模块,这些可编程分子系统能够感知分子输入,计算有关这些输入的决策,并对其环境采取行动。为了管理系统的复杂性并提供模块化,该项目将建立抽象层次结构,其中包括用于编程结构和行为的相关高级语言,将高级代码转换为可合成DNA序列列表的编译器,以及可以预测序列性能的分析软件。 这将允许分子程序员在实验室合成之前指定,设计和验证其系统的正确性。除了这些软件工具外,该项目还将研究分子算法理论,以了解基于信息的分子系统的潜力和局限性,是什么使它们能够有效地执行任务,以及如何有效地设计和分析它们。该项目将把这一基础研究成果付诸实践,并将在实际应用中探索生物系统探测的分子仪器和纳米级器件的可编程制造等。该项目将通过建立一个由学生、教师、研究人员、科学家和工程师组成的多元化社区,扩大从事分子编程工作的科学家和工程师的网络。该社区将通过创建可公开访问的软件工具,课程,教科书,研讨会,教程,本科生研究竞赛和科普视频来培养,以教授分子编程的原理和方法,并吸引年轻研究人员和公众参与这一令人兴奋的新领域。与相关生物技术公司和其他高科技公司的工业伙伴关系将确保将产生的知识迅速转移到现实世界的产品中。 也许最重要的是,随着分子编程成为一种广泛应用的技术,它有可能用新的复杂纳米结构材料改变工业,用集成和自主控制反应来改变化学,用先进的分子仪器来改变生物学,用更复杂的诊断和治疗来改变医疗保健。
项目成果
期刊论文数量(9)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Effective design principles for leakless strand displacement systems
- DOI:10.1073/pnas.1806859115
- 发表时间:2018-12-26
- 期刊:
- 影响因子:11.1
- 作者:Wang, Boya;Thachuk, Chris;Soloveichik, David
- 通讯作者:Soloveichik, David
Automated sequence-level analysis of kinetics and thermodynamics for domain-level DNA strand-displacement systems
- DOI:10.1098/rsif.2018.0107
- 发表时间:2018-12-01
- 期刊:
- 影响因子:3.9
- 作者:Berleant, Joseph;Berlind, Christopher;Winfree, Erik
- 通讯作者:Winfree, Erik
Verifying chemical reaction network implementations: A pathway decomposition approach
验证化学反应网络的实现:路径分解方法
- DOI:10.1016/j.tcs.2017.10.011
- 发表时间:2017
- 期刊:
- 影响因子:1.1
- 作者:Shin, Seung Woo;Thachuk, Chris;Winfree, Erik
- 通讯作者:Winfree, Erik
Towards space- and energy-efficient computations
迈向空间和能源高效的计算
- DOI:
- 发表时间:2019
- 期刊:
- 影响因子:0
- 作者:Condon, Anne;Thachuk, Chris
- 通讯作者:Thachuk, Chris
A domain-level DNA strand displacement reaction enumerator allowing arbitrary non-pseudoknotted secondary structures
- DOI:10.1098/rsif.2019.0866
- 发表时间:2020-06-24
- 期刊:
- 影响因子:3.9
- 作者:Badelt, Stefan;Grun, Casey;Winfree, Erik
- 通讯作者:Winfree, Erik
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Erik Winfree其他文献
Single-Molecule Tracking of Nanorobots on Pseudo-One-Dimensional DNA Origami Tracks
- DOI:
10.1016/j.bpj.2009.12.3206 - 发表时间:
2010-01-01 - 期刊:
- 影响因子:
- 作者:
Nicole Michelotti;Anthony J. Manzo;Alex Johnson-Buck;Kyle Lund;Jeanette Nangreave;Nadine Dabby;Steven Taylor;Renjun Pei;Milan N. Stojanovic;Erik Winfree;Hao Yan;Nils G. Walter - 通讯作者:
Nils G. Walter
Driving DNA Tweezers with an in vitro Transcriptional Oscillator
- DOI:
10.1016/j.bpj.2009.12.2334 - 发表时间:
2010-01-01 - 期刊:
- 影响因子:
- 作者:
Eike Friedrichs;Jongmin Kim;Ralf Jungmann;Elisa Franco;Richard Murray;Erik Winfree;Friedrich C. Simmel - 通讯作者:
Friedrich C. Simmel
Layered Tile Model-Error Reduction for DNA Tile Self-Assembly
分层瓦片模型 - DNA 瓦片自组装的误差减少
- DOI:
- 发表时间:
2005 - 期刊:
- 影响因子:0
- 作者:
Satoshi Murata;Kenichi Fujibayashi;David Zhang;Erik Winfree - 通讯作者:
Erik Winfree
DNAタイルアセンブリのエラー抑制手法
DNA 瓦片组装的错误抑制技术
- DOI:
- 发表时间:
2007 - 期刊:
- 影响因子:0
- 作者:
藤林健一;David Yu Zhang;Erik Winfree;村田智 - 通讯作者:
村田智
Erik Winfree的其他文献
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{{ truncateString('Erik Winfree', 18)}}的其他基金
FET: Small: Exploring the Computational Power of Stochastic Processes in Molecular Information Technology
FET:小型:探索分子信息技术中随机过程的计算能力
- 批准号:
2008589 - 财政年份:2020
- 资助金额:
$ 500万 - 项目类别:
Standard Grant
NSF Student Travel Grant for DNA24: The 24th International Conference on DNA Computing and Molecular Programming
DNA24 的 NSF 学生旅费资助:第 24 届 DNA 计算和分子编程国际会议
- 批准号:
1844818 - 财政年份:2018
- 资助金额:
$ 500万 - 项目类别:
Standard Grant
SHF: Small: A reconfigurable architecture for digital circuit computation by fast, robust, and leakless DNA strand displacement cascades
SHF:小型:通过快速、稳健且无泄漏的 DNA 链位移级联进行数字电路计算的可重构架构
- 批准号:
1718938 - 财政年份:2017
- 资助金额:
$ 500万 - 项目类别:
Standard Grant
Speaker support for workshop on advances in molecular programming and computing
分子编程和计算进展研讨会的演讲者支持
- 批准号:
1340383 - 财政年份:2013
- 资助金额:
$ 500万 - 项目类别:
Standard Grant
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
- 批准号:
1213127 - 财政年份:2012
- 资助金额:
$ 500万 - 项目类别:
Standard Grant
SHF:Medium:Collaborative Research:Scaling Up Programmable and Algorithmic DNA Self-Assembly
SHF:中:合作研究:扩大可编程和算法 DNA 自组装
- 批准号:
1162589 - 财政年份:2012
- 资助金额:
$ 500万 - 项目类别:
Standard Grant
Future directions for molecular programming: DNA17 special session
分子编程的未来方向:DNA17 特别会议
- 批准号:
1143993 - 财政年份:2011
- 资助金额:
$ 500万 - 项目类别:
Standard Grant
Collaborative Research: The Molecular Programming Project
合作研究:分子编程项目
- 批准号:
0832824 - 财政年份:2008
- 资助金额:
$ 500万 - 项目类别:
Continuing Grant
Collaborative Research: EMT/MISC: Behavior Based Molecular Robotics
合作研究:EMT/MISC:基于行为的分子机器人
- 批准号:
0829805 - 财政年份:2008
- 资助金额:
$ 500万 - 项目类别:
Standard Grant
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- 项目类别:面上项目
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