Development of a neuron model based on DNAzyme regulation.
Development of a neuron model based on DNAzyme regulation.
复制标题
基于DNAzyme调节的神经元模型的开发
DOI：
10.1039/d0ra10515e
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发表时间：
2021-03-05
期刊：
影响因子：
3.9
通讯作者：
Wang B
中科院分区：
文献类型：
--
作者：
Chen C;Wu R;Wang B
基于DNA分子电路的神经网络在分子信息处理和人工智能系统中起着重要的作用。事实上，某些DNA分子系统在DNA酶的帮助下可以成为动态单元。当输入信号发生变化时，复杂的DNA电路会自发地产生相应的反馈行为。然而，大多数已报道的DNA神经网络已实现的支点介导的链置换（TMSD）的方法。因此，开发一种利用TMSD机制并添加一种机制来解释DNA酶的调节的方法来构建神经网络是很重要的。在这项研究中，我们设计了一个由DNA酶控制的DNA神经元模型。我们提出了一种基于DNA酶调节神经功能的方法，结合两种反应机制：DNA酶消化和TMSD。利用DNAzyme调整，构建了模拟神经元特性的各个组件。通过改变神经元模型的输入和权值，验证了神经元计算功能的正确性。此外，为了验证神经元在特定功能中的应用潜力，成功实现了投票机。该模型构造简单，可扩展性强，在构建大型神经网络中具有很大的应用潜力。
Neural networks based on DNA molecular circuits play an important role in molecular information processing and artificial intelligence systems. In fact, some DNA molecular systems can become dynamic units with the assistance of DNAzymes. The complex DNA circuits can spontaneously induce corresponding feedback behaviors when their inputs changed. However, most of the reported DNA neural networks have been implemented by the toehold-mediated strand displacement (TMSD) method. Therefore, it was important to develop a method to build a neural network utilizing the TMSD mechanism and adding a mechanism to account for modulation by DNAzymes. In this study, we designed a model of a DNA neuron controlled by DNAzymes. We proposed an approach based on the DNAzyme modulation of neuronal function, combing two reaction mechanisms: DNAzyme digestion and TMSD. Using the DNAzyme adjustment, each component simulating the characteristics of neurons was constructed. By altering the input and weight of the neuron model, we verified the correctness of the computational function of the neurons. Furthermore, in order to verify the application potential of the neurons in specific functions, a voting machine was successfully implemented. The proposed neuron model regulated by DNAzymes was simple to construct and possesses strong scalability, having great potential for use in the construction of large neural networks.
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