SHF: Small: Experimental and Theoretical Development of Error Correction and Digitalization Concepts for Multi-Enzyme Biomolecular Computing Networks

人们正在研究生物计算系统，以进行多阶段信息处理，应用范围从新型生物传感器到创伤/损伤情况下的信号和快速决策、植入性设备、生物燃料电池，最后是生物有机体与硅电子设备的接口。这项研究计划旨在推进主要基于酶的逻辑门的实验设计和理论建模/优化，以及开发非布尔和生物启发的网络元素工具箱。将开发实现互连网络的方法，以及将生化逻辑与生物电子系统连接的方法。为提高生物化学逻辑网络在降噪、健壮性、容错性和可伸缩性方面的性能，将为信息处理应用程序设计模型。因此，本项目将推进利用生物分子，主要是酶，从单一的门到多元素网络来扩大信息处理的基础科学。该研究计划包括基于酶的生化门及其联网的实验调查以及对概念和结果的理论分析。这项工作的实验方面将包括酶系统的选择和联网，这些系统执行不同复杂程度的生化信号的逻辑处理。理论部分将包括生物计算系统的优化和计算机模拟，以确保其稳定和容错运行。我们将具体讨论生物分子信息处理系统的降噪和健壮性。即使是中等复杂性的生物计算元件也将允许复杂的生理系统与纳米结构材料和/或电子设备之间的有效接口。因此，这项研究的更广泛影响将包括推进一种新的新兴技术范式：将涉及生化过程的信息处理阶段联网。我们的目标是拆除电线和电池，减少在可植入设备和其他生物技术应用中现场进行的信息处理阶段对电力供应的总体需求，并促进新的生物传感器概念的发展。通过培训博士后和教育博士生、提供本科生研究项目、K-12外展和开发新的课程，将产生重大的教育影响。

Biocomputing systems are being researched for multi-stage information processing in applications ranging from novel biosensors, to signaling and fast decision making in cases of trauma/injury, implantable devices, biofuel cells, and ultimately, interfacing of living organisms with Si electronics. This research program aims at advancing experimental design and theoretical modeling/optimization of primarily enzyme-based logic gates, as well as developing a toolbox of non-Boolean and bio-inspired network elements. Approaches will be developed for realizing interconnected networks, as well as for interfacing biochemical logic with bioelectronic systems. Models will be devised for improving the performance of biochemical logic networks in terms of noise reduction, robustness, fault-tolerance, and scalability, for information processing applications. Thus, the present project will advance the basic science of scaling up information processing with biomolecules, primarily, with enzymes, beyond single gates to multi-element networks. The research plan involves both experimental investigations of enzyme-based biochemical gates and their networking as well as theoretical analysis of the concepts and results. Experimental aspects of the work will include the selection and networking of enzymatic systems performing logic processing of biochemical signals at various levels of complexity. The theoretical part will encompass optimization and computer simulation of the biocomputing systems to ensure their stable and fault-tolerant operation. We will specifically address noise reduction and robustness of biomolecular information processing systems. Biocomputing elements of even moderate complexity will allow effective interfacing between complex physiological systems and nanostructured materials and/or electronic devices. Thus, the broader impacts of this research will include the advancement of a new emerging technological paradigm: Networking of information processing stages that involve biochemical processes. We aim at taking out the wires and batteries, and reducing the overall need for electrical power supplies at those stages of information processing that are carried out on-site in implantable devices and other biotechnology applications, as well as contributing to the advancement of novel biosensor concepts. Significant educational impact will be achieved by training of postdocs and educating Ph.D. students, offering undergraduate research projects, K-12 outreach, and developing new coursework.