Name
Abstract | ||
|---|---|---|
Abstract—DNA computing relies on biochemical reactions of DNA molecules and may result in incorrect or undesirable computations. Therefore, much work has focused on designing the DNA sequences to make the molecular computation more reliable. Sequence design involves with a number of heterogeneous and conflicting design criteria and traditional optimization methods may face difficulties. In this paper, we formulate the DNA sequence design as a multiobjective optimization problem and solve it using a constrained multiobjective evolutionary algorithm (EA). The method is implemented into the DNA sequence design system, NACST/Seq, with a suite of sequence-analysis tools to help choose the best solutions among many alternatives. The performance of NACST/Seq is compared with other sequence design methods, and analyzed on a traveling salesman problem solved by bio-lab experiments. Our experimental results show that the evolutionary sequence design by NACST/Seq outperforms in its reliability the existing sequence design techniques such as conventional EAs, simulated annealing, and specialized heuristic methods. Index Terms—DNA computing, DNA sequence design, multiob- |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/TEVC.2005.844166 | IEEE Transactions on Evolutionary Computation |
Keywords | Field | DocType |
evolutionary computation,traveling salesman problem,multiobjective evolutionary optimization,dna computing,multiobjective evolutionary algorithm (moea),biochemical reactions,reliable dna computing,dna sequence design system,nucleic acid computing simulation toolkit/sequence generator (nacst/seq),nacst/seq,molecular computation,sequence design,multiob- jective evolutionary algorithm moea,existing sequence design technique,conflicting design criterion,dna sequence,sequence design method,dna sequence design,evolutionary sequence design,sequence-analysis tools,multiobjective optimization problem,dna molecule,dna,biocomputing,nucleic acid computing simulation toolkit/sequence generator nacst/seq.,index terms—dna computing,dna sequences,multiobjective optimization,evolutionary algorithm,design method,simulated annealing,computer simulation,design methodology,design optimization,algorithm design and analysis,constraint optimization,nucleic acid,sequence analysis,indexing terms,sequences | Simulated annealing,Heuristic,Mathematical optimization,Evolutionary algorithm,Computer science,Evolutionary computation,Algorithm,Travelling salesman problem,Genetic algorithm,DNA computing,Sequence analysis | Journal |
Volume | Issue | ISSN |
9 | 2 | 1089-778X |
Citations | PageRank | References |
60 | 3.26 | 24 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Soo-Yong Shin | 1 | 196 | 17.20 |
| In-Hee Lee | 2 | 128 | 10.10 |
| Dongmin Kim | 3 | 60 | 3.26 |
| Byoung-Tak Zhang | 4 | 1571 | 158.56 |