DNA计算的应用与展望

DNA 计算机是当前研究的热点问题，我国的研究刚刚起步，本文详细论述了DNA序列的概念及性质，DNA计算的原理，同时介绍了DNA计算的研究进展概况。     

DNA芯片在最短公共超串问题中的应用

DNA芯片技术是近年来生命科学与信息科学的新兴研究领域，其突出特点在于它的高度并行性、多样化、微型化以及自动化，最短公共超串问题是计算机科学中的NP-完全问题．笔者在DNA计算和DNA芯片基础上，提出了基于DNA芯片解决最短公共超串问题的DNA计算新模型．该模型可对信息高度并行获取，并且具有操作易自动化的优点．     

DNA芯片在最短公共超串问题中的应用

DNA芯片技术是近年来生命科学与信息科学的新兴研究领域,其突出特点在于它的高度并行性、多样化、微型化以及自动化.最短公共超串问题是计算机科学中的NP-完全问题.笔者在DNA计算和DNA芯片基础上,提出了基于DNA芯片解决最短公共超串问题的DNA计算新模型.该模型可对信息高度并行获取,并且具有操作易自动化的优点.     

DNA粘接计算模型及其应用

DNA计算是应用分子生物技术进行计算的新方法。应用形式语言及自动机理论技术研究DNA计算理论,有利于推动理论计算科学的发展。本文根据DNA分子的结构及特点给出了DNA分子的形式化描述,介绍了DNA粘接计算模型的文法结构和计算能力,并应用DNA计算方法求解3-SAT问题。     

DNA计算的研究现状与展望

基于硅材料的微电子技术由于工艺技术和基本理论上的局限,使得现有电子计算机无法满足科技发展对计算能力的需求.由于具有超强的并行运算能力和巨大的数据存储能力,DNA计算始终是新型计算机领域研究的热门.DNA计算的研究已经涉及到DNA计算模型、 DNA计算机系统、 DNA计算的应用等诸多方面.文章从DNA计算流程、DNA计算模型、DNA计算机、DNA计算应用研究等几个方面,综述了DNA计算研究的现状.同时,也指出了DNA计算存在的问题,并从DNA编码设计、DNA计算噪声控制等方面阐述了未来研究方向.相信随着生物技术、纳米技术等的进一步发展,DNA计算一定能够发挥出自身的优势和潜力,能够为国防建设、信息安全、基础科学研究、生命科学研究等方面提供更好的服务.     

走近未来的DNA计算机

DNA计算机的概念和主要特点 利用特定的DNA结构--DNA核酶可以构建各种DNA分子逻辑门,这为DNA计算机的发展奠定了基础.DNA计算是计算机科学和分子生物学相结合而发展起来的新兴研究领域.而DNA计算机是一种生物形式的计算机.它是利NDNA（脱氧核糖核酸）建立的一种完整的信息技术形式，以编码的DNA序列（通常意义上计算机内存）为运算对象，     

DNA计算中编码问题的研究

编码是DNA计算的开始,对DNA计算尤为的重要。编码的好坏直接影响计算反应过程的质量。本文简要描述了DNA编码的理论,总结了编码的约束条件和几个模型的DNA序列的设计。最后,指出了编码问题的研究方向。     

DNA计算技术进展

论述DNA计算技术进展。先介绍DNA计算的基本原理,论述DNA计算的特点方法和存在的问题,接着介绍DNA计算的国内外研究现状,最后指出DNA计算研究中需要解决的问题。     

解决NP问题的DNA编码技术

NP问题是密码学中的一个难题,用DNA计算解决NP问题是目前DNA密码研究的一个热点。文章阐述了DNA编码问题及约束条件,归纳出用DNA计算解决NP问题的基本步骤,分析了Adleman解决哈密尔顿回路问题的实验中DNA编码的质量,提出了可选的更好的编码,并总结了目前DNA编码研究中存在的问题。     

DNA计算问题的研究进展

DNA计算是近十年发展起来的一门新学科,目前的研究已经取得了很大的进展.本文首先介绍了DNA计算的机理,然后说明了DNA分子的结构及DNA计算的特点.最后分析了目前DNA计算所存在的问题,并展望了DNA计算的应用发展前景.     

DNA计算机

脱氧核糖核酸（简称DNA）是生物体内的一种具有双螺旋结构的遗传物质,用DNA可以进行运算,即构成的DNA计算机能很快地求解复杂的问题;以DNA编码为信息的载体,DNA计算机中的输入和输出设备都是DNA的,链用一系列二进制的数代表所求问题中的变量,用DNA中特有的寡核苷酸序列表示这些二进制的数,再将DNA利用分子生物和化学组装技术组装到芯片上,利用DNA杂交化学方法,排除各种代表不正确解的寡核苷酸序列,最后通过聚合酶链式反应（PCR）和各种检测技术读出保留在芯片上的DNA序列,读出的DNA序列所代表的二进制数即为所求问题的解,本文将从DNA运算过程入手,介绍DNA计算机的原理和DNA计算机的若干最新研究进展。     

DNA media storage

In 1994, University of Southern California computer scientist, Dr. Leonard Adleman solved the Hamiltonian path problem using DNA as a computational mechanism. He proved the principle that DNA computing could be used to solve computationally complex problems. Because of the limitations in discovery time, resource requirements, and sequence mismatches, DNA computing has not yet become a commonly accepted practice. However, advancements are continually being discovered that are evolving the field of DNA computing. Practical applications of DNA are not restricted to computation alone. This research presents a novel approach in which DNA could be used as a means of storing files. Through the use of multiple sequence alignment combined with intelligent heu- ristics, the most probabilistic file contents can be determined with minimal errors.     

DNA media storage

In 1994, University of Southern California computer scientist Dr. Leonard Adleman solved the Hamiltonian path problem using DNA as a computational mechanism. He proved the principle that DNA computing could be used to solve computationally complex problems. Because of the limitations in discovery time, resource requirements, and sequence mismatches, DNA computing has not yet become a commonly accepted practice. However, advancements are continually being discovered that are evolving the field of DNA computing. Practical applications of DNA are not restricted to computation alone. This research presents a novel approach in which DNA could be used as a means of storing files. Through the use of multiple sequence alignment combined with intelligent heuristics, the most probabilistic file contents can be determined with minimal errors.     

Genetic algorithm in DNA computing： A solution to the maximal clique problem

Genetic algorithm is one of the possible ways tobreak the limit of brute-force method in DNA computing.Using the idea of Darwinian evolution, we introduce a geneticDNA computing algorithm to solve the maximal clique prob-lem. All the operations in the algorithm are accessible withtoday‘s molecular biotechnoiogy. Our computer simulationsshow that with this new computing algorithm, it is possible toget a solution from a very small initial data pool, avoidingenumerating all candidate solutions. For randomly generatedproblems, genetic algorithm can give correct solution withina few cycles at high probability. Although the current speedof a DNA computer is slow compared with silicon computers,our simulation indicates that the number of cycles needed inthis genetic algorithm is approximately a linear function ofthe number of vertices in the network. This may make DNAcomputers more powerfully attacking some hard computa-tional problems.     

基于分子重组技术的DNA计算

DNA计算是计算科学和分子生物学相结合的新领域。目前关于DNA计算的研究主要是抽象的计算模型和简单的原理性试验。DNA剪接计算模型是以生物DNA分子重组技术为基础的文法系统。本文主要介绍DNA剪接计算模型的文法结构及计算方法,证明了DNA剪接模型可以计算所有图灵机可计算函数。     

A DNA based model for addition computation

Much effort has been made to solve computing problems by using DNA-an organic simulating method, which in some cases is preferable to the current electronic computer. However, No one at present has proposed an effective and applicable method to solve addition problem with molecular algorithm due to the difficulty in solving the carry problem which can be easily solved by hardware of an electronic computer. In this article, we solved this problem by employing two kinds of DNA strings, one is called result and operation string while the other is named carrier. The result and operation string contains some carry information by its own and denotes the ultimate result while the carrier is just for carrying use. The significance of this algorithm is the original code, the fairly easy steps to follow and the feasibility under current molecular biological technology.     

A surface-based DNA algorithm for the minimal vertex cover problem

Abstract DNA computing was proposed for solving a class of intractable computational problems, of which the computing timewill grow exponentially with the problem size. Up to now, many achievements have been made to improve its performance and increase itsreliability. It has been shown many times that the surface-based DNA computing technique has very low error rate, but the technique hasnot been widely used in the DNA computing algorithms design. In this paper, a surface-based DNA computing algorithm for minimal ver-tex cover problem, a problem well-known for its exponential difficulty, is introduced. This work provides further evidence for the abilityof surface-based DNA computing in solving NP-complete problems.     

自组装DNA计算研究难点与展望

随着DNA计算领域研究的深入,自装组DNA计算的研究成为了并行计算领域的研究热点,在本文中,作者主要分析讲述当前自组装DNA计算的几种结构形式：一维的、二维的以及三维的自组装DNA分子结构特点和发展现状,并且提出现在自组装DNA计算发展的难点以及今后的发展展望。随着多学科交叉融合力度的加大,自组装DNA计算将会成为生物信息学、应用数学、计算机仿真学、智能计算、纳米材料科学等多领域专家的重要研究方向。