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An Optimized Ant System Approach for DNA Sequence Optimization

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Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living (IWANN 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5518))

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Abstract

DNA computing is a new computing paradigm which uses bio-molecules as information storage media and biochemical tools as information processing operators. This field has shown many successful and promising results for various applications. Since DNA reactions are probabilistic in nature, different result could be produced even in the same situations, which can be regarded as errors in computing. In order to overcome the drawbacks, many works have focused on the design or error-minimized DNA sequence to improve the reliability of DNA computing. Although the design of DNA sequences is dependent on the protocol of biological experiments, it is highly required to establish a method for the systematic design of DNA sequences, which could be applied to various design constraints. In the previous paper, Ant System approach has been proposed to solve the DNA sequence optimization problem. In this paper, the optimized parameters of Ant System approach are searched to improve the performance of the Ant System for DNA sequence optimization.

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References

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Authors and Affiliations

  1. Center for Artificial Intelligence and Robotics (CAIRO), Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Malaysia

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

Authors
  1. Tri Basuki Kurniawan
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  2. Zuwairie Ibrahim
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  3. Noor Khafifah Khalid
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  4. Marzuki Khalid
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Editor information

Editors and Affiliations

  1. Graduate School of Engineering, Osaka Prefecture University, Osaka, Japan

    Sigeru Omatu

  2. Department of Informatics / CCTC, University of Minho, Braga, Portugal

    Miguel P. Rocha

  3. MAmI Research Lab, University of Castilla-La Mancha,, Ciudad Real, Spain

    José Bravo

  4. Department of Informatics, University of Vigo, Ourense, Spain

    Florentino Fernández

  5. Grupo de Investigación GICAP, Área de Lenguajes Higher Polytechnic School, Universidad de Burgos, Burgos, Spain

    Emilio Corchado

  6. Higher Polytechnic School, University of Burgos, Burgos, Spain

    Andrés Bustillo

  7. Department of Informatics, University of Salamanca, Salamanca, Spain

    Juan M. Corchado

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© 2009 Springer-Verlag Berlin Heidelberg

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Kurniawan, T.B., Ibrahim, Z., Khalid, N.K., Khalid, M. (2009). An Optimized Ant System Approach for DNA Sequence Optimization. In: Omatu, S., et al. Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living. IWANN 2009. Lecture Notes in Computer Science, vol 5518. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02481-8_63

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  • DOI: https://doi.org/10.1007/978-3-642-02481-8_63

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02480-1

  • Online ISBN: 978-3-642-02481-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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