Multi-objective carrier chaotic evolutionary algorithm for DNA sequences design

DNA computing is a new vista of computation, which is of biochemical type. Since each piece of information is encoded in biological sequences, their design is crucial for successful DNA computation. DNA sequence design is involved with a number of design criteria, which is difficult to be solved by the traditional optimization methods. In this paper, the multi-objective carrier chaotic evolution algorithm (MCCEA) is introduced to solve the DNA sequence design problem. By merging the chaotic search base on power function carrier, a set of good DNA sequences are generated. Furthermore, the simulation results show the efficiency of our method.     

Multi-objective carrier chaotic evolutionary algorithm for DNA sequences design

DNA computing is a new vista of computation, which is of biochemical type. Since each piece of information is encoded in biological sequences, their design is crucial for successful DNA computation. DNA sequence design is involved with a number of design criteria, which is difficult to be solved by the traditional optimization methods. In this paper, the multi-objective carrier chaotic evolution algorithm (MCCEA) is introduced to solve the DNA sequence design problem. By merging the chaotic search base on power function carrier, a set of good DNA sequences are generated. Furthermore, the simulation results show the efficiency of our method.     

Improved taboo search algorithm for designing DNA sequences

The design of DNA sequences is one of the most practical and important research topics in DNA computing. We adopt taboo search algorithm and improve the method for the systematic design of equal-length DNA sequences, which can satisfy certain combinatorial and thermodynamic constraints. Using taboo search algorithm, our method can avoid trapping into local optimization and can find a set of good DNA sequences satisfying required constraints.     

Improved taboo search algorithm for designing DNA sequences

The design of DNA sequences is one of the most practical and important research topics in DNA computing. We adopt taboo search algorithm and improve the method for the systematic design of equal-length DNA sequences, which can satisfy certain combinatorial and thermodynamic constraints. Using taboo search algorithm, our method can avoid trapping into local optimization and can find a set of good DNA sequences satisfying required constraints.     

DNA计算及DNA计算机的研究进展

概述了DNA计算的基本原理、DNA计算的应用和DNA计算机的研究进展及存在问题，基于DNA生化反应的计算机称为DNA计算机，由于其采用一种完全不同于传统计算机的运算逻辑与存贮方式，DNA计算机在解决某些复杂问题时具有传统计算机无法比拟的优势，目前国际上关于DNA计算和DNA分子生物计算机的研究方兴未艾，极大地推进了DNA计算机的研究过程。     

A novel DNA computing model based on RecA-mediated triple-stranded DNA structure

The field of DNA computing emerged in 1994 after Adleman’s paper was published. Henceforth,a few scholars solved some noted NP-complete problems in this way. And all these methods of DNA computing are based on conventional Watson-Crick hydrogen bond of doublehelical DNA molecule. In this paper, we show that the triple-stranded DNA structure mediated by RecA protein can be used for solving computational problems. Sequence-specific recognition of double-stranded DNA by oligonucleotide-directed triple helix (triplex) formation is used to carry out the algorithm. We present procedure for the 3-vertex-colorability problems. In our proposed procedure, it is suggested that it is possible to solve more complicated problems with more variables by this model.     

图的最小顶点覆盖问题的质粒DNA计算模型

给出了图的最小顶点覆盖问题的质粒DNA算模型及其实现算法．算法的时间复杂性是O(q),编码最小覆盖问题所需的核苷酸片段种类为n,其中n,q分别是图的规模和边数．在算法中,所用酶的种类也等于图的规模．而且,算法不需要复杂的单链DNA自身退火反应和PCR扩增．     

一种DNA计算系统的有限自动机模型

通过一个实例给出了粘贴系统模型的基本定义，讨论了粘贴系统模型的正则文法特性，并从自动机的角度给出了相当于正则文法表达能力的有限自动机模型。     

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。     

New algorithms for some NP-optimization problems by DNA computing

There are lots of DNA computation models now. The model developed by Martyn Amos' group is special in its error-resistant property, but unfortunately, its computational power is limited and cannot solve optimization problems efficiently. In this paper, some new methods have been introduced to enlarge the computational power of this model. And based on these new methods, several DNA algorithms have been designed to solve some NP-optimization problems such as minimal vertex cover, maximal clique and MAX-3SAT.     

解决图着色问题的膜进化算法

图着色问题是图论中比较热门的NP难问题之一。针对该问题,有许多启发式求解算法,但都存在求解的质量不高,计算时间较长等问题。近些年提出的膜进化算法,在处理NP难问题中展现出了独特的优势。基于膜进化算法框架,提出了解决图着色问题的膜进化算法,把图着色问题和膜结合,设计了复制、融合、分裂、溶解、融合分裂、禁忌搜索6种膜进化算子。这些算子在演变的过程中使膜和膜结构发生进化,从而找到更优解,最后求得解决方案。在DIMACS的40个挑战数据集上面进行了实验,与3个最新的图着色算法比较的结果表明：在保证解的质量的情况下,文中提出的膜进化算法能有效降低求解的时间,其中有58%的实例占优。     

A global heuristically search algorithm for DNA encoding

A new efficient algorithm is developed to design DNA words with equal length for DNA computing. The algorithm uses a global heuristic optimizing search approach and converts constraints to a carry number to accelerate the convergence, which can generate a DNA words set satisfying some thermodynamic and combinatorial constraints. Based on the algorithm, a software for DNA words design is developed.     

A global heuristically search algorithm for DNA encoding

A new efficient algorithm is developed to design DNA words with equal length for DNA computing. The algorithm uses a global heuristic optimizing search approach and converts constraints to a carry number to accelerate the convergence, which can generate a DNA words set satisfying some thermodynamic and combinatorial constraints. Based on the algorithm, a software for DNA words design is developed.     

A DNA sequence alignment algorithm using quality information and a fuzzy inference method

DNA sequence alignment algorithms in computational molecular biology have been improved by diverse methods. In this paper, we propose a DNA sequence alignment that uses quality information and a fuzzy inference method developed based on characteristics of DNA fragments and a fuzzy logic system in order to improve conventional DNA sequence alignment methods that uses DNA sequence quality information. In conventional algorithms, DNA sequence alignment scores are calculated by the global sequence alignment algorithm proposed by Needleman-Wunsch, which is established by using quality information of each DNA fragment. However, there may be errors in the process of calculating DNA sequence alignment scores when the quality of DNA fragment tips is low, because only overall DNA sequence quality information are used. In our proposed method, an exact DNA sequence alignment can be achieved in spite of low quality of DNA fragment tips by improvement of conventional algorithms using quality information. Mapping score parameters used to calculate DNA sequence alignment scores are dynamically adjusted by the fuzzy logic system utilizing lengths of DNA fragments and frequencies of low quality DNA bases in the fragments. From the experiments by applying real genome data of National Center for Biotechnology Information, we could see that the proposed method is more efficient than conventional algorithms.     

A DNA sequence alignment algorithm using quality information and a fuzzy inference method

DNA sequence alignment algorithms in computational molecular biology have been improved by diverse methods. In this paper, we propose a DNA sequence alignment that uses quality information and a fuzzy inference method developed based on the characteristics of DNA fragments and a fuzzy logic system in order to improve conventional DNA sequence alignment methods that uses DNA sequence quality information. In conventional algorithms, DNA sequence alignment scores are calculated by the global sequence alignment algo- rithm proposed by Needleman-Wunsch, which is established by using quality information of each DNA fragment. However, there may be errors in the process of calculating DNA sequence alignment scores when the quality of DNA fragment tips is low, because only the overall DNA sequence quality information are used. In our proposed method, an exact DNA sequence alignment can be achieved in spite of the low quality of DNA fragment tips by improvement of conventional algorithms using quality information. Mapping score param- eters used to calculate DNA sequence alignment scores are dynamically adjusted by the fuzzy logic system utilizing lengths of DNA fragments and frequencies of low quality DNA bases in the fragments. From the experiments by applying real genome data of National Center for Biotechnology Information, we could see that the proposed method is more efficient than conventional algorithms.     

基于生物芯片技术的地图四着色问题的DNA算法

基于先进的生物芯片技术、多种荧光标记技术和DNA计算理论提出了解决地图四着色问题的DNA算法,通过一个实例阐述了具体的DNA操作步骤,并对生化实验进行了计算机模拟,给出了所有可行的着色方案,证明了该算法的可行性。与已有的模型相比,该模型在解的准确性、计算复杂度以及操作的自动化方面都表现出了很强的优势。     

基于稀疏技术的序列运算方法

序列运算过程中经常遇到稀疏序列之间的相互运算。针对序列运算的计算优化问题,该文首先分析了序列稀疏性的成因,并分析了序列运算理论中不同类型基本运算对于序列稀疏性的影响,同时给出了相应的计算结果序列的稀疏度估算公式。然后,根据序列与序列运算的特点,将稀疏技术应用于序列运算中,提出了通用存储方法与特征存储方法等2种稀疏序列存储技术。最后,利用算例对所提出的稀疏序列存储方法加以检验,采用稀疏技术后不同类型序列运算的时间开销均有不同程度的降低,特别是卷和、交积、并积与序除运算的计算时间下降为原来的6%~38%,算例结果表明了该文工作的正确性与应用价值。     

Molecular logic computing model based on self-assembly of DNA nanoparticles

In this paper, a logic computing model was constructed using a DNA nanoparticle, combined with color change technology of DNA/Au nanoparticle conjugates, and DNA computing. Several important technologies are utilized in this molecular computing model: DNA self-assembly, DNA/Au nanoparticle conjugation, and the color change resulting from Au nanoparticle aggregation. The simple logic computing model was realized by a color change, resulting from changing of DNA self-assembly. Based on this computing model, a set of operations computing model was also established, by which a simple logic problem was solved. To enlarge the applications of this logic nanocomputing system, a molecular detection method was developed for H1N1 virus gene detection.     

DNA序列的一种分类方法

基于小波变换和相关技术,提出了一种DNA序列的分类方法.首先将DNA序列转换成数字序列,然后对此序列进行Matlab快速分解,计算未知类别序列与已知类别序列的相关系数,由此判定序列的类别.结果表明,该方法是切实可行的.     

基于闭环DNA的边着色问题DNA算法

提出一种新的DNA计算模型——闭环DNA计算模型。引进了批删除实验。讨论了其实现过程;提出并证明了边着色问题的基本定理,设计并实现了闭环DNA计算算法．该算法将边的DNA编码分为两部分,一部分存储边和色位置的二维数据,另一部分存储色号值;在DNA计算的主体部分用批删除实验得到全部正常的边着色,并通过电泳实验和检测实验获得χ′^-正常边着色．举例说明了算法的有效性和可行性．