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Implementation of an ant colony system for DNA sequence optimization

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Abstract

DNA computation exploits the computational power inherent in molecules for information processing. However, in order to perform the computation correctly, a set of good DNA sequences is crucial. A lot of work has been carried out on designing good DNA sequences to archive a reliable molecular computation. In this article, the ant colony system (ACS) is introduced as a new tool for DNA sequence design. In this approach, the DNA sequence design is modeled as a path-finding problem, which consists of four nodes, to enable the implementation of the ACS. The results of the proposed approach are compared with other methods such as the genetic algorithm.

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Authors and Affiliations

  1. Centre for Artificial Intelligence and Robotics (CAIRO), Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310 UTM, Skudai, Johor Darul Takzim, Malaysia

    Zuwairie Ibrahim, Tri Basuki Kurniawan, Noor Khafifah Khalid, Shahdan Sudin & Marzuki Khalid

Authors
  1. Zuwairie Ibrahim
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  2. Tri Basuki Kurniawan
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  3. Noor Khafifah Khalid
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  4. Shahdan Sudin
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  5. Marzuki Khalid
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Corresponding author

Correspondence to Zuwairie Ibrahim.

Additional information

This work was presented in part at the 14th International Symposium on Artificial Life and Robotics, Oita, Japan, February 5–7, 2009

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Ibrahim, Z., Kurniawan, T.B., Khalid, N.K. et al. Implementation of an ant colony system for DNA sequence optimization. Artif Life Robotics 14, 293–296 (2009). https://doi.org/10.1007/s10015-009-0683-0

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  • DOI: https://doi.org/10.1007/s10015-009-0683-0

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