scholarly journals Multiobjective Evolutionary Optimization of DNA Sequences for Reliable DNA Computing

2005 ◽  
Vol 9 (2) ◽  
pp. 143-158 ◽  
Author(s):  
S.-Y. Shin ◽  
I.-H. Lee ◽  
D. Kim ◽  
B.-T. Zhang
Keyword(s):  
Dna Sequences ◽  
Dna Computing ◽  
Evolutionary Optimization

Prediction of Visibility Under Radiation Fog by DNA Computing

2020 ◽  
Vol 16 (02) ◽  
pp. 231-254
Author(s):  
Mandrita Mondal ◽  
Kumar S. Ray
Keyword(s):  
Wind Speed ◽  
Dna Sequences ◽  
Dna Computing ◽  
Fuzzy Reasoning ◽  
Rate Of Change ◽  
Dew Point ◽  
Radiation Fog ◽  
Implication Operator ◽  
Point Spread ◽  
Wet Lab

In this paper, we propose a wet lab algorithm for prediction of visibility under radiation fog by DNA computing. The model is based on a concept of similarity based fuzzy reasoning suitable for wet lab implementation. The concept of similarity based fuzzy reasoning using DNA sequences is different from conventional approach to fuzzy reasoning. It replaces the logical aspect of classical fuzzy reasoning by DNA chemistry. By the proposed algorithm the tedious job to choose suitable implication operator, which is absolutely necessary for classical fuzzy reasoning, can be avoided. If the fuzzified forms of five observed parameters, i.e. dew point, dew point spread, the rate of change of dew point spread per day, wind speed and sky condition are given, the newly proposed algorithm efficiently predicts the possibility of visibility under radiation fog. The final result of the wet lab algorithm, which is in form of fuzzy DNA, produces multi valued status which can be linguistically interpreted to match the perception of an expert.

CLASSIFICATION OF SODAR DATA BY DNA COMPUTING

2011 ◽  
Vol 07 (03) ◽  
pp. 413-432 ◽  
Author(s):  
KUMAR S. RAY ◽  
MANDRITA MONDAL
Keyword(s):  
Similarity Measure ◽  
Dna Sequences ◽  
Dna Computing ◽  
Present Model ◽  
Fuzzy Reasoning ◽  
Sodar Data ◽  
Double Stranded Dna ◽  
Wet Lab ◽  
Measure Of Similarity

In this paper, we propose a wet lab algorithm for classification of SODAR data by DNA computing. The concept of DNA computing is essentially exploited to generate the classifier algorithm in the wet lab. The classifier is based on a new concept of similarity-based fuzzy reasoning suitable for wet lab implementation. This new concept of similarity-based fuzzy reasoning is different from conventional approach to fuzzy reasoning based on similarity measure and also replaces the logical aspect of classical fuzzy reasoning by DNA chemistry. Thus, we add a new dimension to the existing forms of fuzzy reasoning by bringing it down to nanoscale. We exploit the concept of massive parallelism of DNA computing by designing this new classifier in the wet lab. This newly designed classifier is very much generalized in nature and apart from SODAR data, this methodology can be applied to other types of data also. To achieve our goal we first fuzzify the given SODAR data in a form of synthetic DNA sequence which is called fuzzy DNA and which handles the vague concept of human reasoning. In the present approach, we can avoid the tedious choice of a suitable implication operator (for a particular operation) necessary for the classical approach to fuzzy reasoning based on fuzzy logic. We adopt the basic notion of DNA computing based on standard DNA operations. We consider double stranded DNA sequences, whereas, most of the existing models of DNA computation are based on single stranded DNA sequences. In the present model, we consider double stranded DNA sequences with a specific aim of measuring similarity between two DNA sequences. Such similarity measure is essential for designing the classifier in the wet lab. Note that, we have developed a completely new measure of similarity based on base pair difference which is absolutely different from the existing measure of similarity and which is very much suitable for expert system approach to classifier design, using DNA computing. In the present model of DNA computing, the end result of the wet lab algorithm produces multi valued status which can be linguistically interpreted to match the perception of an expert.

scholarly journals Correcting Errors in Image Encryption Based on DNA Coding

Molecules ◽  
2018 ◽  
Vol 23 (8) ◽  
pp. 1878 ◽  
Author(s):  
Bin Wang ◽  
Yingjie Xie ◽  
Shihua Zhou ◽  
Xuedong Zheng ◽  
Changjun Zhou
Keyword(s):  
Image Encryption ◽  
Dna Sequences ◽  
Dna Computing ◽  
Experimental Results ◽  
Primary Method ◽  
Image Information ◽  
Dna Coding ◽  
Encryption And Decryption ◽  
Novel Method

As a primary method, image encryption is widely used to protect the security of image information. In recent years, image encryption pays attention to the combination with DNA computing. In this work, we propose a novel method to correct errors in image encryption, which results from the uncertainty of DNA computing. DNA coding is the key step for DNA computing that could decrease the similarity of DNA sequences in DNA computing as well as correct errors from the process of image encryption and decryption. The experimental results show our method could be used to correct errors in image encryption based on DNA coding.

scholarly journals An Image Encryption Scheme Based on DNA Computing and Cellular Automata

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Shihua Zhou ◽  
Bin Wang ◽  
Xuedong Zheng ◽  
Changjun Zhou
Keyword(s):  
Cellular Automata ◽  
Image Encryption ◽  
Dna Sequences ◽  
Dna Computing ◽  
Simulation Experiment ◽  
Brute Force ◽  
Image Information ◽  
Key Space ◽  
Encryption Algorithms ◽  
Differential Attacks

Networks have developed very quickly, allowing the speedy transfer of image information through Internet. However, the openness of these networks poses a serious threat to the security of image information. The field of image encryption has drawn attention for this reason. In this paper, the concepts of 1-dimensional DNA cellular automata and T-DNA cellular automata are defined, and the concept of reversible T-DNA cellular automata is introduced. An efficient approach to encryption involving reversible T-DNA cellular automata as an encryption tool and natural DNA sequences as the main keys is here proposed. The results of a simulation experiment, performance analysis, and comparison to other encryption algorithms showed this algorithm to be capable of resisting brute force attacks, statistical attacks, and differential attacks. It also enlarged the key space enormously. It meets the criteria for one-time pad and resolves the problem that one-time pad is difficult to save.

DNA as an Engineering Material: From Assembly to Computation on Silicon

2011 ◽  
Vol 1346 ◽  
Author(s):  
Hayri E. Akin ◽  
Jiebin Zhong ◽  
Miroslav Penchev ◽  
Cengiz S. Ozkan ◽  
Mihrimah Ozkan
Keyword(s):  
Dna Sequences ◽  
Self Assembly ◽  
Dna Computing ◽  
Microarray Platform ◽  
Differential Resistance ◽  
Building Blocks ◽  
Boolean Formula ◽  
Electrical Measurements ◽  
Tunneling Diodes ◽  
Dna Strands

ABSTRACTDNA possesses inherent recognition and self-assembly capabilities, making it attractive templates for constructing functional material structures as building blocks for nanoelectronics. Here we report the use of DNA towards the assembly and electronic functionality of nanoarchitectures based on conjugates of carbon nanotubes (CNTs), nanowires (NWs) and DNA computing on Si-CMOS platform. First, assembly of CNTs with DNA is demonstrated and electrical measurements of these nanoarchitectures demonstrate negative differential resistance in the presence of CNT/DNA interfaces, which indicates a biomimetic route to fabricating resonant tunneling diodes. End-to-end assembly of NWs is realized with designed DNA sequences and process is carried on silicon CMOS based microarray platform. Second, this microarray platform is adopted to perform DNA computing. To begin with, the information present in an image is encoded through the concentrations of various DNA strands via selective hybridization and decoded on microarray to recreate the original image. Lately, various satisfiability (SAT) problems, which has long served as a benchmark problem in DNA computing, are solved on this platform via DNA. The goal in a SAT Problem is to determine appropriate assignments of a set of Boolean variables with values of either “true” or “false” such that the output of the whole Boolean formula is true. Other than making 1st time silicon compatible DNA computing, our studies make us understand bio molecules, especially DNA has various advantages for future hybrid technologies.

scholarly journals Stable DNA Sequence Over Close-Ending and Pairing Sequences Constraint

2021 ◽  
Vol 12 ◽  
Author(s):  
Xue Li ◽  
Ziqi Wei ◽  
Bin Wang ◽  
Tao Song
Keyword(s):  
Dna Sequence ◽  
Optimization Algorithm ◽  
Dna Sequences ◽  
Dna Computing ◽  
Predator Prey ◽  
Minimum Value ◽  
Molecular Biotechnology ◽  
Current Minimum ◽  
Sine And Cosine Functions

DNA computing is a new method based on molecular biotechnology to solve complex problems. The design of DNA sequences is a multi-objective optimization problem in DNA computing, whose objective is to obtain optimized sequences that satisfy multiple constraints to improve the quality of the sequences. However, the previous optimized DNA sequences reacted with each other, which reduced the number of DNA sequences that could be used for molecular hybridization in the solution and thus reduced the accuracy of DNA computing. In addition, a DNA sequence and its complement follow the principle of complementary pairing, and the sequence of base GC at both ends is more stable. To optimize the above problems, the constraints of Pairing Sequences Constraint (PSC) and Close-ending along with the Improved Chaos Whale (ICW) optimization algorithm were proposed to construct a DNA sequence set that satisfies the combination of constraints. The ICW optimization algorithm is added to a new predator–prey strategy and sine and cosine functions under the action of chaos. Compared with other algorithms, among the 23 benchmark functions, the new algorithm obtained the minimum value for one-third of the functions and two-thirds of the current minimum value. The DNA sequences satisfying the constraint combination obtained the minimum of fitness values and had stable and usable structures.

Experimental Validation of DNA Sequences for DNA Computing: Use of a SYBR Green I Assay

2006 ◽  
pp. 248-256 ◽  
Author(s):  
Wendy K. Pogozelski ◽  
Matthew P. Bernard ◽  
Salvatore F. Priore ◽  
Anthony J. Macula
Keyword(s):  
Dna Sequences ◽  
Dna Computing ◽  
Experimental Validation ◽  
Sybr Green ◽  
Sybr Green I

Trajectory Planning of Mobile Robots Using DNA Computing

2004 ◽  
Vol 8 (3) ◽  
pp. 295-301 ◽  
Author(s):  
Kazuo Kiguchi ◽  
◽  
Keigo Watanabe ◽  
Toshio Fukuda ◽  
Keyword(s):  
Mobile Robots ◽  
Trajectory Planning ◽  
Dna Sequences ◽  
Dna Computing ◽  
Goal Section ◽  
Work Area ◽  
Start Section ◽  
Electronic Computers ◽  
Dna Computers ◽  
Optimal Trajectory Planning

DNA computers are attracting increasing attention as next-generation replacements for conventional electronic computers. Computation is realized using the chemical reaction of DNA. This paper presents optimal trajectory planning for mobile robots using DNA computing. The working area of a mobile robot is divided into many sections and the shortest trajectory avoiding obstacles in the work area is calculated by DNA computing. The location of obstacles is known in advance. In DNA computing, Watson-Crick pairing is used to find this trajectory. DNA sequences representing locations of obstacles are removed in this process. The shortest DNA molecule that begins with the start section and terminates with the goal section represents the shortest trajectory avoiding obstacles in the robot’s work area. The proposed algorithm is especially effective with a DNA molecular computer.

Sign in / Sign up

Export Citation Format

Share Document