SHF: Small :Digital Signal Processing with Biomolecular Reactions
SHF:小型:生物分子反应的数字信号处理
基本信息
- 批准号:1117168
- 负责人:
- 金额:$ 40万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2011
- 资助国家:美国
- 起止时间:2011-08-01 至 2014-07-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Digital signal processing has been a cornerstone of the modern communications and electronics revolution, transforming application areas such as wired and wireless communications, storage, and biomedical signal processing. This project will study digital signal processing in an entirely new domain: molecular systems. In contrast to electronic systems, where signals are represented by time-varying voltage values, in molecular systems signals are represented by time-varying concentrations of different molecular types, such as proteins, RNA and DNA. This project will develop, implement, and evaluate molecular-level designs for a variety of digital signal processing operations such as filtering, equalization, and noise cancellation. These operations will be synchronized by clock signals, created through sustained chemical oscillations. Memory will be created by transferring signals between different molecular types in alternating phases of the clock. The key idea underpinning this research is that the computation should be essentially rate-independent: it should only depend on coarse categories for the rates of the chemical reactions (e.g., ?fast? vs. ?slow?). It should not matter how fast any ?fast? reaction is ? only that ?fast? reactions are fast relative to ?slow? reactions. Designs with this property can be mapped to different chemical substrates. They compute accurately in spite of variations in environmental conditions such as temperature. The impetus for this work is not computation per se; chemical systems will never be useful for number crunching. Rather the field of molecular computing aims for the design of custom, embedded biological ?sensors? and ?controllers? ? viruses and bacteria that are engineered to perform useful tasks in situ, such as cancer detection and drug therapy. As an experimental chassis, this project will map designs for digital signal processing operations to chemical reactions involving DNA strands. These designs will be evaluated with computer simulations of the chemical kinetics.Techniques for analyzing the dynamics of biological systems are well established. However, synthesizing computation with such mechanisms requires new techniques ? and an entirely new mindset. The digital circuit design community has unique expertise that can be brought to bear on the challenging design problems encountered in synthetic biology. Applications in biology, in turn, offer a wealth of interesting problems in algorithmic development. With its cross-disciplinary emphasis, this project will bring new perspectives to both fields.If successful, the proposed research will transform disciplines such as genetic engineering of drug-delivery systems. Currently, a costly, ineffective ad-hoc approach prevails. With robust and rate-independent techniques for implementing operations such as digital signal processing, much more effective systems will be developed. An important goal of the project is to communicate the impetus for interdisciplinary research to a wide audience. A new course will be developed, titled "Circuits, Computation, and Biology" offered jointly through the Electrical Engineering Department and the Biomedical Informatics and Computational Biology Program at the University of Minnesota. Building upon current recruitment efforts that have brought in female students, students from underrepresented groups will be recruited into the project.
数字信号处理一直是现代通信和电子革命的基石,改变了有线和无线通信、存储和生物医学信号处理等应用领域。该项目将研究一个全新领域的数字信号处理:分子系统。电子系统中的信号由随时间变化的电压值表示,而分子系统中的信号由不同分子类型(例如蛋白质、RNA 和 DNA)随时间变化的浓度表示。 该项目将开发、实施和评估用于各种数字信号处理操作(例如滤波、均衡和噪声消除)的分子级设计。这些操作将通过持续化学振荡产生的时钟信号同步。记忆将通过在时钟交替相位的不同分子类型之间传输信号来创建。 支持这项研究的关键思想是计算本质上应该与速率无关:它应该只依赖于化学反应速率的粗略类别(例如,“快”与“慢”)。多快并不重要。反应是?仅此而已?快?反应快相对于“慢”?反应。具有这种特性的设计可以映射到不同的化学基材上。尽管温度等环境条件发生变化,它们仍能准确计算。这项工作的动力不是计算本身;而是计算。化学系统永远无法用于数字运算。相反,分子计算领域的目标是设计定制的嵌入式生物“传感器”。和?控制器? ?病毒和细菌被设计为在原位执行有用的任务,例如癌症检测和药物治疗。作为一个实验底盘,该项目将把数字信号处理操作的设计映射到涉及 DNA 链的化学反应。这些设计将通过化学动力学的计算机模拟进行评估。分析生物系统动力学的技术已经很成熟。然而,用这种机制综合计算需要新技术?和全新的心态。数字电路设计界拥有独特的专业知识,可以解决合成生物学中遇到的具有挑战性的设计问题。反过来,生物学中的应用为算法开发提供了大量有趣的问题。由于其跨学科重点,该项目将为这两个领域带来新的视角。如果成功,拟议的研究将改变药物输送系统基因工程等学科。目前,普遍采用成本高昂、效率低下的临时方法。通过用于实现数字信号处理等操作的稳健且与速率无关的技术,将开发出更有效的系统。该项目的一个重要目标是向广大受众传达跨学科研究的动力。将开发一门名为“电路、计算和生物学”的新课程,由明尼苏达大学电气工程系和生物医学信息学和计算生物学项目联合提供。在目前招收女学生的努力的基础上,来自代表性不足群体的学生将被招募到该项目中。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Keshab Parhi其他文献
Keshab Parhi的其他文献
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{{ truncateString('Keshab Parhi', 18)}}的其他基金
Collaborative Research: SHF: Small: Efficient and Scalable Privacy-Preserving Neural Network Inference based on Ciphertext-Ciphertext Fully Homomorphic Encryption
合作研究:SHF:小型:基于密文-密文全同态加密的高效、可扩展的隐私保护神经网络推理
- 批准号:
2243053 - 财政年份:2023
- 资助金额:
$ 40万 - 项目类别:
Standard Grant
Collaborative Research: SHF: Medium: TensorNN: An Algorithm and Hardware Co-design Framework for On-device Deep Neural Network Learning using Low-rank Tensors
合作研究:SHF:Medium:TensorNN:使用低秩张量进行设备上深度神经网络学习的算法和硬件协同设计框架
- 批准号:
1954749 - 财政年份:2020
- 资助金额:
$ 40万 - 项目类别:
Continuing Grant
SHF: Small: Collaborative Research: LDPD-Net: A Framework for Accelerated Architectures for Low-Density Permuted-Diagonal Deep Neural Networks
SHF:小型:协作研究:LDPD-Net:低密度置换对角深度神经网络加速架构框架
- 批准号:
1814759 - 财政年份:2018
- 资助金额:
$ 40万 - 项目类别:
Standard Grant
EAGER: Low-Energy Architectures for Machine Learning
EAGER:机器学习的低能耗架构
- 批准号:
1749494 - 财政年份:2017
- 资助金额:
$ 40万 - 项目类别:
Standard Grant
SHF: Small: Advanced Digital Signal Processing with DNA
SHF:小型:采用 DNA 的先进数字信号处理
- 批准号:
1423407 - 财政年份:2014
- 资助金额:
$ 40万 - 项目类别:
Standard Grant
SaTC: STARSS: Design of Secure and Anti-Counterfeit Integrated Circuits
SaTC:STARSS:安全防伪集成电路设计
- 批准号:
1441639 - 财政年份:2014
- 资助金额:
$ 40万 - 项目类别:
Standard Grant
SHF: Small: Digital Signal Processing using Stochastic Computing
SHF:小型:使用随机计算的数字信号处理
- 批准号:
1319107 - 财政年份:2013
- 资助金额:
$ 40万 - 项目类别:
Standard Grant
EAGER: Synthesizing Signal Processing Functions with Biochemical Reactions
EAGER:利用生化反应综合信号处理功能
- 批准号:
0946601 - 财政年份:2009
- 资助金额:
$ 40万 - 项目类别:
Standard Grant
Collaborative Research: CPA-DA: Noise-Aware VLSI Signal Processing: A New Paradigm for Signal Processing Integrated Circuit Design in Nanoscale Era
合作研究:CPA-DA:噪声感知VLSI信号处理:纳米时代信号处理集成电路设计的新范式
- 批准号:
0811456 - 财政年份:2008
- 资助金额:
$ 40万 - 项目类别:
Continuing Grant
Design of High-Speed DSPTransceivers for Ethernet over Copper
铜缆以太网高速 DSP 收发器的设计
- 批准号:
0429979 - 财政年份:2004
- 资助金额:
$ 40万 - 项目类别:
Standard Grant
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