Strand design for biomolecular computation
Theoretical Computer Science - Natural computing
DNA sequence design using templates
New Generation Computing
PUNCH: An Evolutionary Algorithm for Optimizing Bit Set Selection
DNA 7 Revised Papers from the 7th International Workshop on DNA-Based Computers: DNA Computing
DNASequencesGenerator: A Program for the Construction of DNA Sequences
DNA 7 Revised Papers from the 7th International Workshop on DNA-Based Computers: DNA Computing
Developing Support System for Sequence Design in DNA Computing
DNA 7 Revised Papers from the 7th International Workshop on DNA-Based Computers: DNA Computing
A PCR-based Protocol for In Vitro Selection of Non-crosshybridizing Oligonucleotides
DNA8 Revised Papers from the 8th International Workshop on DNA Based Computers: DNA Computing
From RNA Secondary Structure to Coding Theory: A Combinatorial Approach
DNA8 Revised Papers from the 8th International Workshop on DNA Based Computers: DNA Computing
Dna computation: Theory, practice, and prospects
Evolutionary Computation
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Biomolecular computing and programming
IEEE Transactions on Evolutionary Computation
Multiobjective evolutionary optimization of DNA sequences for reliable DNA computing
IEEE Transactions on Evolutionary Computation
Implementation of Binary Particle Swarm Optimization for DNA Sequence Design
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part II: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living
Improving the design of sequences for DNA computing: A multiobjective evolutionary approach
Applied Soft Computing
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Hybridization between a DNA sequence and its base-pairing complement is crucial to retrieve the information stored in DNA sequences and operate a computation operation in DNA computing. Therefore, much works have focused on designing the DNA sequences to archive a reliable molecular computation and many algorithms have been proposed to obtain a set of good DNA sequences. In this paper, Ant Colony System (ACS) is proposed to solve the DNA sequence design problem. ACS as a derivate from Ant Colony Optimization (ACO) is an improvement from Ant System (AS) that used some agents to get their solutions based on the pheromone in their colony. A model is prepared which consists of four nodes representing four DNA bases using nearest-neighbor thermodynamic parameter's Watson-Crick base pair ΔG°37 as the distance between nodes. The results of the proposed approach are compared with the other methods such as genetic algorithm and evolutionary algorithm.