SHF: Small :Digital Signal Processing with Biomolecular Reactions

数字信号处理已经成为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。这个项目将研究数字信号处理在一个全新的领域：分子系统。在电子系统中，信号由时变电压值表示，而在分子系统中，信号由不同分子类型（如蛋白质、RNA和DNA）的时变浓度表示。该项目将开发、实施和评估各种数字信号处理操作的分子级设计，如滤波、均衡和噪声消除。这些操作将由时钟信号同步，由持续的化学振荡产生。记忆将通过在时钟的交替阶段在不同分子类型之间传递信号而产生。支撑这项研究的关键思想是，计算基本上应该是速率无关的：它应该只依赖于化学反应速率的粗略类别（例如，“快速”）。与慢?)。不管有多快，快？反应是？就这么快？反应相对于？慢？快？反应。具有这种特性的设计可以映射到不同的化学基材上。尽管环境条件（如温度）发生变化，它们仍能准确计算。这项工作的推动力并不是计算本身；化学系统永远不会对数字运算有用。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?？ 病毒和细菌被设计成在原位执行有用的任务，如癌症检测和药物治疗。作为一个实验基础，这个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。这些设计将用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，用这种机制进行综合计算需要新的技术。以及一种全新的心态。数字电路设计界具有独特的专业知识，可以对合成生物学中遇到的具有挑战性的设计问题承担责任。反过来，在生物学中的应用为算法开发提供了大量有趣的问题。该项目强调跨学科，将为这两个领域带来新的视角。如果成功，拟议中的研究将改变药物输送系统的基因工程等学科。目前，普遍采用的是一种代价高昂、效率低下的临时办法。有了稳健且与速率无关的技术来实现数字信号处理等操作，将开发出更有效的系统。该项目的一个重要目标是将跨学科研究的动力传达给广泛的受众。将开发一门名为“电路、计算和生物学”的新课程，由明尼苏达大学电子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基础上，该项目将招收来自代表性不足群体的学生。

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.