Department of Electronics and Communication Engineering, SRM University - AP, Andhra Pradesh, India.
Department of Biology, SRM University - AP, Andhra Pradesh, India.
IET Syst Biol. 2020 Dec;14(6):343-349. doi: 10.1049/iet-syb.2020.0060.
Dynamic biological systems can be modelled to an equivalent modular structure using Boolean networks (BNs) due to their simple construction and relative ease of integration. The chemotaxis network of the bacterium () is one of the most investigated biological systems. In this study, the authors developed a multi-bit Boolean approach to model the drifting behaviour of the chemotaxis system. Their approach, which is slightly different than the conventional BNs, is designed to provide finer resolution to mimic high-level functional behaviour. Using this approach, they simulated the transient and steady-state responses of the chemoreceptor sensory module. Furthermore, they estimated the drift velocity under conditions of the exponential nutrient gradient. Their predictions on chemotactic drifting are in good agreement with the experimental measurements under similar input conditions. Taken together, by simulating chemotactic drifting, they propose that multi-bit Boolean methodology can be used for modelling complex biological networks. Application of the method towards designing bio-inspired systems such as nano-bots is discussed.
动态生物系统可以通过布尔网络 (BNs) 建模为等效的模块化结构，因为它们的结构简单，并且相对容易集成。细菌的趋化网络 () 是研究最多的生物系统之一。在这项研究中，作者开发了一种多位布尔方法来模拟 趋化系统的漂移行为。他们的方法与传统的 BNs 略有不同，旨在提供更高的分辨率来模拟高级功能行为。使用这种方法，他们模拟了化学感受器感觉模块的瞬态和稳态响应。此外，他们还在指数营养梯度条件下估计了漂移速度。他们对趋化漂移的预测与相似输入条件下的实验测量结果非常吻合。总之，通过模拟趋化漂移，他们提出多位布尔方法可用于模拟复杂的生物网络。还讨论了该方法在设计仿生系统（如纳米机器人）方面的应用。
