scholarly journals A membrane evolutionary algorithm for DNA sequence design in DNA computing

2012 ◽  
Vol 57 (6) ◽  
pp. 698-706 ◽  
Author(s):  
JianHua Xiao ◽  
XingYi Zhang ◽  
Jin Xu
Keyword(s):  
Evolutionary Algorithm ◽  
Dna Sequence ◽  
Dna Computing ◽  
Sequence Design ◽  
Dna Sequence Design

Improved Multi-Objective Particle Swarm Optimization Algorithm for DNA Sequence Design

2020 ◽  
Vol 15 (12) ◽  
pp. 1450-1459
Author(s):  
Ying Niu ◽  
Hangyu Zhou ◽  
Shida Wang ◽  
Kai Zhao ◽  
Xiaoxiao Wang ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Evolutionary Algorithm ◽  
Dna Sequence ◽  
Dna Sequences ◽  
Particle Swarm ◽  
Experimental Simulation ◽  
Swarm Optimization ◽  
Sequence Design ◽  
Multi Objective ◽  
Dna Sequence Design

The DNA sequence design is a vital step in reducing undesirable biochemical reactions and incorrect computations in successful DNA computing. To this end, many studies had concentrated on how to design higher quality DNA sequences. However, DNA sequences involve some thermodynamic and conflicting conditions, which in turn reflect the evolutionary algorithm process implemented through chemical reactions. In the present study, we applied an improved multi-objective particle swarm optimization (IMOPSO) algorithm to DNA sequence design, in which a chaotic map is combined with this algorithm to avoid falling into local optima. The experimental simulation and statistical results showed that the DNA sequence design method based on IMOPSO has higher reliability than the existing sequence design methods such as traditional evolutionary algorithm, invasive weed algorithm, and specialized methods.

Hierarchy Evolutionary Searching Algorithm for DNA Encoding Sequence

2010 ◽  
Vol 20-23 ◽  
pp. 94-98
Author(s):  
Lian Ye ◽  
Jing Chen ◽  
Yong Kang Xing
Keyword(s):  
Dna Sequence ◽  
Dna Sequences ◽  
Dna Computing ◽  
Reaction Process ◽  
Dna Encoding ◽  
Molecular Computation ◽  
Sequence Design ◽  
Dna Sequence Design ◽  
Molecular Reaction

DNA sequence design is the basic and important step for DNA computing. Good codeword could avoid some error may possibly occurred in practical computing. Therefore, much work has focused on designing the DNA sequences to make the molecular computation more reliable. In this paper, a new hierarchy evolutionary searching algorithm is proposed to obtain good DNA encoding sequences, this approach is based on combinatorial constraints which affect the molecular reaction process, and can provide some reliable and effective encoding sequences for controllable DNA computing.

Evolutionary Multi-Objective Optimization for DNA Sequence Design

2011 ◽  
pp. 239-264
Author(s):  
Soo-Yong Shin ◽  
In-Hee Lee ◽  
Byoung-Tak Zhang
Keyword(s):  
Evolutionary Algorithms ◽  
Dna Sequence ◽  
Dna Sequences ◽  
Dna Microarrays ◽  
Superior Performance ◽  
Final Decision ◽  
Sequence Design ◽  
Multi Objective ◽  
Dna Sequence Design ◽  
Np Problems

Finding reliable and efficient DNA sequences is one of the most important tasks for successful DNArelated experiments such as DNA computing, DNA nano-assembly, DNA microarrays and polymerase chain reaction. Sequence design involves a number of heterogeneous and conflicting design criteria. Also, it is proven as a class of NP problems. These suggest that multi-objective evolutionary algorithms (MOEAs) are actually good candidates for DNA sequence optimization. In addition, the characteristics of MOEAs including simple addition/deletion of objectives and easy incorporation of various existing tools and human knowledge into the final decision process could increase the reliability of final DNA sequence set. In this chapter, we review multi-objective evolutionary approaches to DNA sequence design. In particular, we analyze the performance of e-multi-objective evolutionary algorithms on three DNA sequence design problems and validate the results by showing superior performance to previous techniques.

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