Research On Optimization Method Of DNA Sequence Design In DNA Computing

DNA computing is a brand news computing mode which is based on DNA molecular and biological enzyme and uses biochemical reaction as its information processing tool. By nature of the advantages of great parallelity, huge storage ability and low power costs, DNA computing reveals its glorious prosperity. As a branch of DNA computing, DNA coding means designing the initial database of DNA computing. Designing of effective DNA code will remarkably improve the reliability of DNA computing.The paper discusses DNA coding and the main focus is on the decreasing of illegal code sequences. To achieve the DNA coding, the paper briefly introduces the thermodynamics and biology restrictions. And then, mathematic model is designed for the restrictions respectively. Moreover, some evolution algorithms are researched. Based on the research mentioned above, two optimal approaches for DNA coding are designed. The structure of the paper is as follows:1. The main restrictions which have influences on the DNA codes designing are studied. Six mathematic restrictions are discussed respectively. There are H-measure, Continuity, Similarity, Hairpin, Tm as well as GC content. Based on six restrictions mentioned above, an optimal model for DNA coding with a multiple aims evaluation system is established. In the paper, the evaluation system is realized as Fitness function.2. An optimal algorithm for DNA coding named discrete particle swarm optimization (DPSO) is researched. First, the location and velocity updating rule is derived according to the DNA coding restrictions and the characteristic of discrete value. And then, in order to evaluate the performance of DNA consequence set, a fitness function based on the six restrictions as well as their respective power is designed. The DPSO algorithm is realized in chapter four. And in contrast with traditional genetic algorithm, the DPSO algorithm remarkably decreases the computing complexity, also, it's very convenient to set and adjust the parameters.3. A more optimal algorithm for DNA coding named cultural-based PSO (CBPSO) is designed. The population space adopts the DPSO and makes use of its rapid evolvement attribute, and sends elite individual to the belief space. Meanwhile, the belief space adopts the genetic operations which is including the selection, crossover and variation operation. The belief space will influences the population space to guide the population space and increase the diversity of the population space as well as the global search ability. Through the realization of the CBPSO algorithm, DNA code sequence with higher quality is derived.4. A General-Purpose Sequence Design System is designed and realized using JAVA language. The system structure contains five layers:behavior layer, algorithm layer, restriction layer, object layer and database layer, and those layers are loose coupled with each other. The good traits contribute to an agile, extendable and general-purposed system. Through the realization of the GPSDS system, different optimal model for DNA coding can be implemented, and the respective DNA code sequence acquired.