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Chemical Reaction Networks' Programming for Solving Equations.
Shang, Ziwei; Zhou, Changjun; Zhang, Qiang.
Affiliation
  • Shang Z; Key Laboratory of Advanced Design and Intelligent Computing, Ministry of Education, School of Software Engineering, Dalian University, Dalian 116622, China.
  • Zhou C; College of Mathematics and Computer Science, Zhejiang Normal University, Jinhua 321004, China.
  • Zhang Q; Key Laboratory of Advanced Design and Intelligent Computing, Ministry of Education, School of Software Engineering, Dalian University, Dalian 116622, China.
Curr Issues Mol Biol ; 44(4): 1725-1739, 2022 Apr 14.
Article in En | MEDLINE | ID: mdl-35723377
ABSTRACT
The computational ability of the chemical reaction networks (CRNs) using DNA as the substrate has been verified previously. To solve more complex computational problems and perform the computational steps as expected, the practical design of the basic modules of calculation and the steps in the reactions have become the basic requirements for biomolecular computing. This paper presents a method for solving nonlinear equations in the CRNs with DNA as the substrate. We used the basic calculation module of the CRNs with a gateless structure to design discrete and analog algorithms and realized the nonlinear equations that could not be solved in the previous work, such as exponential, logarithmic, and simple triangle equations. The solution of the equation uses the transformation method, Taylor expansion, and Newton iteration method, and the simulation verified this through examples. We used and improved the basic calculation module of the CRN++ programming language, optimized the error in the basic module, and analyzed the error's variation over time.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Curr Issues Mol Biol Journal subject: BIOLOGIA MOLECULAR Year: 2022 Type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Curr Issues Mol Biol Journal subject: BIOLOGIA MOLECULAR Year: 2022 Type: Article Affiliation country: China