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DNA computing is a new field of research in computer science and molecular biology combined developed DNA as computing tools,using powerful parallel computing ability of the DNA reaction successfully resolved,such as the minimum spanning tree,such as the maximum Clique NP problems.Founder of DNA computing is Leonard Adelaide Lyman Professor,University of Southern California,in1994,using DNA computing method to solve a well-known mathematical problem,namely the seven vertices Hamilton Path Problem. Recently,scientists began using DNA.The calculations to create a biological computer,the DNA molecule on the human body or in vivo,to operate it,the calculation results can be read through fluorescent protein activities.DNA computing is the use of the double helix structure of DNA base pairing law to encode information,that will be the object of the operation is mapped to a single DNA molecule,the biological action of the enzyme to generate a variety of data pool,and then the original data in accordance with certain rules controlled biochemical reaction process operation highly parallel mapping into a DNA molecule chain. Finally,the use of molecular biological techniques (such as polymerase chain reaction PCR ultrasonic degradation,purified by affinity chromatography,cloning, mutagenesis,molecular,electrophoresis,magnetic bead separation,etc.),the detection,the calculation result for.This article focuses on the specific analysis of the fluorescent technology applications and three types of problems the DNA surface computing model,the basic algorithm,surface algorithm,error,and the resulting problems,more comprehensive introduction to the surface of the DNA computing model an overview of the specific contents are as follows:Hamilton problems surface DNA computing:the the Hamilton problem is a classic problem in graph theory. Seeking a given vertex Hamilton problems,the traditional method of DNA computing in the solution state,through the efficient and rapid characteristics of biochemical reactions,generate all possible solution.Its significant advantage is that fully reflects the high degree of parallelism of DNA computing. However,the drawback is that it is not easy to control the mismatch rate and the generation of spurious solutions as well as the final solution.Surface solid state DNA computing is generally encoded chain fixed to the surface and to identify DNA chain representatives Solutions by biochemical operation.Surface DNA computing satisfiability problem:mark on the surface of the DNA molecule,DNA immobilization and hybridization using fluorescence techniques,will represent all possible solution exists different DNA sequences immobilized on a solid surface,and then by the number of hybrid and the degradation process to filter out the correct solution can be detected by fluorescent labeling each and the final result of the calculation.0-1programming problems surface DNA computing:First,for each constraint inequality,road code combinations,and then its surface has been labeled the corresponding DNA complement links,we will find,meet the appropriate chain of inequalities solutions with the corresponding complementary strand for hybridization with fluorescently labeled to produce different colors of fluorescence,and finally through the fluorescence imaging techniques can observe the results and record feasible solution.Now,nearly a wide range of applications of DNA computing to various fields of science,but also there are many deficiencies and shortcomings,such as calculation errors and coding confusion,we need to improve them.The last part of this paper,the calculation of DNA computing,as well as DNA surface is summarized in,to point out some areas for improvement,which a clear direction for our next study.
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