Verma Arjun, Fratto Brian E, Privman Vladimir, Katz Evgeny
Department of Physics, Clarkson University, Potsdam, NY 13699, USA.
Department of Chemistry and Biomolecular Science, Clarkson University, Potsdam, NY 13699, USA.
Sensors (Basel). 2016 Jul 5;16(7):1042. doi: 10.3390/s16071042.
We consider flow systems that have been utilized for small-scale biomolecular computing and digital signal processing in binary-operating biosensors. Signal measurement is optimized by designing a flow-reversal cuvette and analyzing the experimental data to theoretically extract the pulse shape, as well as reveal the level of noise it possesses. Noise reduction is then carried out numerically. We conclude that this can be accomplished physically via the addition of properly designed well-mixing flow-reversal cell(s) as an integral part of the flow system. This approach should enable improved networking capabilities and potentially not only digital but analog signal-processing in such systems. Possible applications in complex biocomputing networks and various sense-and-act systems are discussed.
我们考虑了已用于二进制操作生物传感器中的小规模生物分子计算和数字信号处理的流动系统。通过设计一个流动反转比色皿并分析实验数据来优化信号测量，以便从理论上提取脉冲形状，并揭示其所含噪声水平。然后进行数值降噪。我们得出结论，这可以通过添加经过适当设计的充分混合的流动反转池作为流动系统的一个组成部分来物理实现。这种方法应该能够提高网络能力，并且在这样的系统中不仅可能实现数字信号处理，还可能实现模拟信号处理。文中讨论了其在复杂生物计算网络和各种传感与动作系统中的可能应用。
