DNA计算中核酸序列设计方法比较研究(英文)

DNA计算是将现实问题进行编码,映射到DNA分子上,然后通过分子生物实验产生出代表问题解的DNA分子,最后通过检测技术提取出该DNA分子．高质量的DNA编码可以尽可能避免或减少计算过程中出现的错误,并使检测阶段易于提取出代表问题解的DNA分子．文中对基于汉明距离和基于自由能的DNA核酸编码方法进行研究,分析了两类方法的约束条件对DNA编码质量的影响,比较了两类方法排除非特异性杂交的完备性和计算量,进一步分析了两类方法编码DNA序列的效率．通过分析和比较得到,两类DNA计算编码方法都能有效地限制DNA分子间的非特异性杂交,其中基于汉明距离的DNA编码方法的计算量比较小,但是它仅能近似地估计DNA分子间杂交的热力学稳定性,不能完全替代最小自由能的编码方法．在满足DNA计算试验精度要求的条件下,采用基于汉明距离的DNA编码设计方法不仅能有效地的挑选出特异性杂交和非特异性杂交的DNA序列,还能有效地减少计算量,从而提高DNA序列设计的效率．     

基于纠错码编码理论的DNA编码研究*

作为一种新的计算模式,DNA计算有着强大的计算能力,编码问题在DNA计算中占据重要的位置,有效的编码设计能够提高DNA计算的可靠性。基于纠错码编码理论,提出了一种新的DNA编码方法,该方法可以找出具有一定长度且满足汉明距离约束的DNA编码序列。最后,给出了该算法的仿真,结果表明了该算法的有效性。     

基于部分字的DNA编码设计与分析*

DNA编码问题是DNA计算中的第一步也是最重要的一步,是DNA计算中的一个基本问题。引入部分字与其洞的定义,研究了部分字的洞与沃森—克里克汉明距离的内在联系,得到沃森—克里克汉明距离与DNA编码的关系;通过分析不完全匹配部分字中洞的出现位置,对发生错误匹配的DNA码进行了优化。解决了DNA编码中除去洞分散分布在DNA双链中的不完全匹配问题,有效弥补了杂交过程中出现的假阳性的缺陷,为DNA编码的研究注入了活力。     

DNA编码问题及其复杂性研究*

高质量的DNA编码可以避免DNA分子间的非特异性杂交,提高DNA计算的有效性和可靠性。首先对DNA编码的约束条件进行归类,分析了各编码约束对编码质量的影响;然后研究了编码质量、编码数量、序列长度与DNA计算可靠性、有效性、可扩充性之间的关系;最后通过类比DNA编码问题和图的独立集问题,说明了求解最大DNA序列集合问题是NP完全的。     

隐私保护DNA序列汉明距离计算问题

DNA序列承载着人体重要的生物学信息，如何在保护隐私的情况下正确地对不同的DNA序列进行比对，成为亟待研究的科学问题。汉明距离在一定程度上刻画了两个DNA序列的相似程度，在保护隐私的情况下，研究DNA序列的汉明距离计算问题。首先定义了DNA序列的0-1编码规则，该规则将长度为n的DNA序列编码成长度为4n的0-1串，证明了两个DNA序列的汉明距离等于它们的0-1编码串的汉明距离的一半。以此结论为基础，以GM加密算法为主要密码学工具，构造了计算DNA序列汉明距离的一个安全两方计算协议。在半诚实攻击者模型下，证明了协议的正确性，给出了基于模拟器的安全性证明，并对协议的效率进行了分析。     

图顶点着色问题的DNA计算模型

DNA计算是以DNA分子作为数据的一种新型计算模式.为了减少DNA计算中编码的数量,不降低生化实验操作的可靠性,文中建立了一种基于酶切技术和PCR技术的图顶点着色DNA计算模型,给出了实现该模型的双编码的编码方案.分析表明,利用酶切技术和PCR技术能够有效删除非解并读取真解.该模型的解的检测方法类似于DNA测序技术,使得该模型更容易实现自动化操作.     

基于闭环DNA的指派问题算法

给出了闭环DNA计算模型及其生化实验。用闭环DNA计算模型设计出了指派问题的DNA算法。首先对决策变量进行二维DNA编码来存放决策变量和效益值，然后通过有目的的终止技术和删除实验得到指派问题的全部可行解，最后通过电泳实验和检测实验获得最优指派问题的最优解。举例说明了算法的可行性。最后，为减少DNA编码数量和缩短DNA编码的码长，讨论了算法的两种改进方法。     

基于动态遗传算法的DNA序列集合设计(英文)

DNA编码序列的质量与数量直接影响着DNA计算的可靠性和规模,如何找到尽可能好的及尽可能多的DNA序列用于实际的应用一直是DNA计算的一个核心问题．文中首先介绍了研究DNA编码和DNA序列集合对DNA计算的意义,并给出了DNA序列设计的汉明距离和反汉明距离约束条件的定义．DNA序列集合的研究对DNA计算的可靠性和规模有着重要的影响,因此文中利用遗传算法和动态遗传算法来设计满足上述约束条件的DNA序列集合,通过对两种方法所得结果的比较,证明了动态遗传算法明显优于遗传算法．与此同时,将文中所得到的实验结果与前人的研究成果进行比较可知,文中的结果大幅提高了DNA编码的上界,从而进一步缩小了DNA编码界的取值范围．并且文中所给出的实验结果,对以后DNA编码的理论界的研究以及编码理论中关于4元码界的研究,提供了重要的参考值．     

基于聚类小生境遗传算法的DNA编码优化

DNA编码优化问题是DNA计算中的核心问题。分析DNA编码优化的约束条件,在单链DNA序列集合上引入h距离,将聚类小生境技术应用于小种群遗传算法的构造,对DNA编码优化问题进行求解。基于h距离定义DNA序列间的相似函数,将碱基字母编码为4进制整数、DNA编码序列作为个体编码为4进制整数向量、种群编码为4进制整数矩阵,基于模4算术运算,构造相应的遗传算子,并给出DNA编码序列的具体计算结果。实验结果表明,与现有DNA编码序列优化结果相比,该算法可得到更好的DNA编码序列且计算效率较高。     

基于文化微粒群优化算法的DNA编码研究

对DNA编码约束进行研究,选择汉明测量以及相似度作为DNA序列集设计的主要约束,并结合连续性约束与GC Content约束,将序列集设计问题抽象为带有强约束的多目标优化问题,采用文化微粒群算法解决该多目标优化问题。仿真结果表明,该混合算法针对DNA编码序列设计问题,在求解最优值能力、解的稳定性方面都能取得较好的效果。     

Automating the DNA computer: solving n-Variable 3-SAT problems

In the decade since the first molecular computation was performed, it has been shown that DNA molecules can perform sophisticated, massively parallel computations avoiding the Von Neumann bottleneck. However, progress in the field has been slow. The largest problem solved to date is an instance of the 20-variable 3-CNF SAT problem. Performing the computation took more than two man-weeks to complete because every aspect of the computation was performed by hand. Molecular computations are extremely labor intensive and error prone–automation is necessary for further progress. The next step, (the second generation DNA computer—that of taking the laborious, laboratory bench protocols performed by hand, and automating them), has been achieved with the construction of an automated DNA computer dubbed EDNAC. It employs the same paradigm that was used to solve the labor-intensive instance of the 20-variable 3-CNF SAT problem. Using a combinatorial DNA library and complementary probes, EDNAC solves instances of the n-variable 3-CNF SAT problem. A 10 variable instance of the 3-CNF SAT problem was essayed. The computation took 28 h to perform. EDNAC correctly computed nine of the 10 variables, with a tenth variable remaining ambiguous. This result is comparable to current results in the molecular computation community. This research tested the critical properties, such as complexity, robustness, reliability, and repeatability necessary for the successful automation of a molecular computer.     

Implementation of an ant colony system for DNA sequence optimization

DNA computation exploits the computational power inherent in molecules for information processing. However, in order to perform the computation correctly, a set of good DNA sequences is crucial. A lot of work has been carried out on designing good DNA sequences to archive a reliable molecular computation. In this article, the ant colony system (ACS) is introduced as a new tool for DNA sequence design. In this approach, the DNA sequence design is modeled as a path-finding problem, which consists of four nodes, to enable the implementation of the ACS. The results of the proposed approach are compared with other methods such as the genetic algorithm.     

Multiplying with DNA

A functional machine is not only an assembly of parts, but also an assembly of processes. The processing of each part must obey laws that respect to the property of this part. For example, building any kind of computer entails selecting appropriate components and assembling their properties to function in computation. Here, we describe computation using a DNA strand as the basic unit and we have used this unit to achieve the function of multiplication. We exploit the phenomenon of DNA hybridization, in which each strand can represent two individual units that can pair to form a single unit. We represent the numbers we multiply in binary, with different lengths representing each digit present in the number. In principle, all combinations of the numbers will be present in solution. Following hybridization, there is present a collection of duplex molecules that are tailed by single-stranded ends. These intermediates are converted to fully duplex molecules by filling in the ends with DNA polymerase. The lengths that are present represent the digits that are present, and they may be separated by denaturing PAGE. The results give a series of bands for each power of two. The number of bands in the size domain for a particular power of two is converted to binary and the sum of all present bands is then added together. Experimentally, the result of this process always yields the correct answer.     

DNA computation simulator based on abstract bases

 We developed a simulator to aid those who design algorithms and protocols for DNA computing. In this simulator, abstract sequences instead of real DNA sequences are used to represent molecules in order to increase efficiency of simulations. Two approaches for simulation are available: threshold and stochastic. The simulator consists of two main parts, one for finding reactions among existing molecules and generating new ones, and the other for numerically solving differential equations to calculate the concentration of each molecule. The two parts rely on each other. In particular for the threshold approach, the former avoids a combinatorial explosion by setting a threshold on concentrations of molecules that can take part in reactions. In addition, the stochastic approach is also available for simulations which are hard by the threshold approach. Some simulation results by the approaches are also presented: computation of Boolean circuits, whiplash PCR, formation of DNA tiles and polymerase chain reaction (PCR). We also integrate simulating DNA computation and fitting parameters by the genetic algorithm (GA), where simulation results are used as evaluation functions for the genetic algorithm. The integration is applied to find good protocols for PCR amplification. A trial to refine the reaction model for hybridization is also described before the final discussion on the simulator.     

DNA分子计算模型

The field of practical DNA computing opened in 1994 with Adleman's paper,in which a laboratory experi-ment involving DNA molecules was used to solve a small instance of the Hamiltonian Path problem. The characteris-tic of this computation is its powerful ability in parallelism,its huge storage and high energy efficiency. This paper mainly introduces the principles of DNA computing and the sticker computing model.     

求解0-1规划问题的DNA计算模型(英文)

DNA计算是以DNA分子作为数据的一种新型计算模式．在DNA计算中首要面对的问题是编码问题．文中提出了一种双编码方法,利用这种编码方法可以使得在DNA计算的读解过程类似于DNA测序过程,容易实现自动化操作．基于该编码方法所建立的DNA计算模型可用于求解0-1规划问题,只需4次PCR反应即可读取问题的可行解．与其他DNA计算模型相比,该模型具有操作简单、易于实现的优点．     

Optofluidic DNA computation based on optically manipulated microdroplets

DNA computing is a promising approach for dealing with biomolecular information. Although several DNA logic circuits which can evaluate biomolecular inputs have been proposed, they have serious drawbacks in the processing speed and the amount of molecules used in implementation. Here, we present optofluidic DNA computation as an effective method for constructing a DNA computing system. By confining the reaction space of DNA computation to the inside of a microdroplet and manipulating a group of droplets with external light signals, we improve usability of DNA computation as well as the processing performance. Optical manipulation is applied to transport the droplets and to initiate DNA computation by forced merging of the droplets. The proposed method has advantages over conventional DNA computation schemes in flexible operations, simultaneous multiplexed evaluation, and processing acceleration. As the first demonstration of optofluidic DNA computation, logical AND and OR operations are performed by optical manipulation of microdroplets which contain either DNA logic gates or input molecules. Also, considerable reduction in the processing time is confirmed on the optofluidic DNA computation owing to reduction of the reaction space to the microdroplet.     

DNA计算机:原理、进展及难点(Ⅱ)计算机"数据库"的形成--DNA分子的合成问题

基于生化反应机理的DNA计算机模型引起了科学领域内许多不同学科学者们的关注与兴趣．DNA计算已经成为国际科学研究前沿领域内的一个新热点．DNA计算机的研制需要诸如生物工程、计算机科学、数学、物理、化学、信息科学、微电子技术、激光技术以及控制科学等许多学科的共同协作攻关．作者以系列文章的形式拟对DNA计算机的基本原理、研究进展、DNA计算的模型以及当前研究中的难点给予研讨．该文属第二篇，重点讨论DNA计算机研制中DNA分子的合成问题．DNA分子的合成问题不仅是DNA计算中生物操作过程首先要处理的问题，而且是DNA计算机研制中必须要解决的问题，因为最终实用化的DNA计算机应是一种全自动化的．如何将DNA分子的合成过程与编码、其它生化操作自动地衔接起来是全自动化DNA计算机当前研究的关键难题．若要解决这个问题，人们必须很熟悉有关DNA分子合成的基本原理以及合成技术．这也是该文的动机．