AF: SHF: Small: Adaptive molecular computation using buffered strand displacement networks

学习和适应是生命系统的基本过程。人类显然有能力学习复杂的概念，但即使是单细胞生物，如细菌，也能够对外部刺激做出适应性反应。这表明，原则上，生物分子的合成系统可以被开发成能够持续运行并表现出类似的适应行为。由于生物技术和纳米技术领域开发的工具取得了进展，现在有可能在实验室中设计这种系统。本项目将研究基于合成DNA的信息处理系统的设计和实验实现，这些系统表现出自适应行为，如学习。这项研究的成功完成将使未来能够开发能够持续运行的合成生化系统，这可能具有实际应用，如长期健康监测，以及提供深入了解生物系统中学习的生化基础。该项目将支持本科生和研究生的培训和教育。该项目将研究使用DNA链置换反应实施的合成生物化学系统中的学习和适应。在DNA链置换反应网络中，多链DNA“门”结构用于处理使用DNA单链编码的信息，通过结合自由扩散的单链并释放其他单链到溶液中作为响应。在这个项目中，将开发一种特殊的DNA链置换门，称为“缓冲门”。缓冲门是一个大量的门开始处于非活动状态，一个子集被激活来执行它们的计算任务：一旦每个门被消耗，除了其通常的输出之外，门还释放一个链来激活缓冲区中的新门，因此活动门的数量大致保持不变。在这个项目中，缓冲门系统将在模拟和实验室中进行研究。至关重要的是，缓冲门系统，其中一个门控制激活链的可用性，另一个缓冲门将进行研究。这将使信息能够存储和更新的分子系统，从而使适应行为。这个概念将被用作基本的设计构建块，以实现能够响应外部提供的输入信号的自适应行为的分子计算系统。该项目的目标将是设计，模拟和实现分子逻辑系统，展示自适应行为，例如，实现监督学习算法。

Learning and adaptation are fundamental processes in living systems. Human beings are clearly capable of learning complex concepts, but even unicellular organisms such as bacteria are capable of adaptive response to external stimuli. This suggests that synthetic systems of biomolecules could, in principle, be developed to enable sustained operation and exhibit similar adaptive behaviors. Thanks to advances in the tools developed in the fields of biotechnology and nanotechnology, it is now becoming possible to engineer such systems in the laboratory. This project will study the design and experimental implementation of synthetic DNA-based information processing systems that exhibit adaptive behaviors such as learning. Successful completion of this research will enable future development of synthetic biochemical systems capable of sustained operation, which could have practical applications such as long-term health monitoring, as well as providing insights into the biochemical basis of learning in biological systems. The project will support training and education of undergraduate and graduate students.This project will study learning and adaptation in synthetic biochemical systems implemented using DNA strand displacement reactions. In DNA strand displacement reaction networks, multi-strand DNA "gate" structures are used to process information that is encoded using single strands of DNA, by binding to freely-diffusing single strands and releasing other single strands into solution in response. In this project, a particular class of DNA strand displacement gates known as "buffered gates" will be developed. A buffered gate is one where a large quantity of gates start in an inactive state and a subset are activated to carry out their computational task: once each gate is consumed, in addition to its usual outputs the gate also releases a strand to activate a new gate from the buffer, so the population of active gates remains roughly constant. In this project, buffered gate systems will be studied in simulation and in the laboratory. Crucially, buffered gate systems in which one gate controls the availability of activating strands for another buffered gate will be studied. This will enable information to be stored and updated with the molecular system, thereby enabling adaptive behavior. This concept will be used as the fundamental design building block to implement molecular computing systems capable of adaptive behavior in response to externally-provided input signals. The goal of this project will be to design, simulate and implement molecular logic systems that demonstrate adaptive behavior, for example, implementing supervised learning algorithms.