An evolutionary Monte Carlo algorithm for predicting DNA hybridization

作者：Kim Joon Shik; Lee Ji Woo; Noh Yung Kyun; Park Ji Yoon; Lee Dong Yoon; Yang Kyung Ae; Chai Young Gyu; Kim Jong Chan; Zhang Byoung Tak^*

来源：Biosystems, 2008, 91(1): 69-75.

DOI：10.1016/j.biosystems.2007.07.005

• DNA computing
• evolutionary algorithm
• Monte Carlo method
• DNA theorem proving

Many DNA-based technologies, such as DNA computing, DNA nanoassembly and DNA biochips, rely on DNA hybridization reactions. Previous hybridization models have focused on macroscopic reactions between two DNA strands at the sequence level. Here, we propose a novel population-based Monte Carlo algorithm that simulates a microscopic model of reacting DNA molecules. The algorithm uses two essential thermodynamic quantities of DNA molecules: the binding energy of bound DNA strands and the entropy of unbound strands. Using this evolutionary Monte Carlo method, we obtain a minimum free energy configuration in the equilibrium state. We applied this method to a logical reasoning problem and compared the simulation results with the experimental results of the wet-lab DNA experiments performed subsequently. Our simulation predicted the experimental results quantitatively.

• 出版日期2008-1
• 单位上海生物信息技术研究中心