A Novel Adaptive Linear Neuron Based on DNA Strand Displacement Reaction Network.

Journal: IEEE/ACM transactions on computational biology and bioinformatics
Published Date:

Abstract

Analog DNA strand displacement circuits can be used to build artificial neural network due to the continuity of dynamic behavior. In this study, DNA implementations of novel catalysis, novel degradation and adjustment reaction modules are designed and used to build an analog DNA strand displacement reaction network. A novel adaptive linear neuron (ADALINE) is constructed by the ordinary differential equations of an ideal formal chemical reaction network, which is built by reaction modules. When reaction network approaches equilibrium, the weights of the ADALINE are updated without learning algorithm. Simulation results indicate that, ADALINE based on the analog DNA strand displacement circuit has ability to implement the learning function of the ADALINE based on the ideal formal chemical reaction networks, and fit a class of linear function.

Authors

  • Chengye Zou
    School of Mathematics and Statistics, Anyang Normal University, Anyang 455000, China.
  • Xiaopeng Wei
    Key Lab of Advanced Design and Intelligent Computing (Ministry of Education), Dalian University, Dalian, China.
  • Qiang Zhang
    Yunan Provincial Center for Disease Control and Prevention, Kunming 650022, China.
  • Changjun Zhou
    College of Computer Science and Engineering, Dalian Minzu University, Dalian, China.