International Journal of Systems Science and Applied Mathematics

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An In-depth Evaluation of an Optimized Algorithm for DNA Motive Discovery

Received: May 29, 2018    Accepted: Jun. 27, 2018    Published: Mar. 07, 2019
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Abstract

Motive Finding is the process of locating the meaningful patterns in the sequence of DNA, RNA or Proteins. There are many widely used algorithms in practice to solve the motive finding problem and these methods are local search methods. Different search algorithms were discussed which are Gibbs sampling, projection, pattern branching, and profile branching. The limitations surrounding them gave an advantage for the selection of the best algorithm in producing an optimized algorithm for the DNA discovery.

DOI 10.11648/j.ijssam.20180304.11
Published in International Journal of Systems Science and Applied Mathematics ( Volume 3, Issue 4, December 2018 )
Page(s) 67-73
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Motive, Optimization, Algorithm, DNA, RNA, Discovery

References
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[8] Reddy S. U., Arock M., and Reddy A. V. (2010). Planted (l, d) – Motive Finding using Particle Swarm Optimization, JCA Special Issue on “Evolutionary Computation for Optimization Techniques” ECOT, 2010.
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  • APA Style

    Amannah Constance Izuchukwu, Ernest Chukwuka Ukwosah. (2019). An In-depth Evaluation of an Optimized Algorithm for DNA Motive Discovery. International Journal of Systems Science and Applied Mathematics, 3(4), 67-73. https://doi.org/10.11648/j.ijssam.20180304.11

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    ACS Style

    Amannah Constance Izuchukwu; Ernest Chukwuka Ukwosah. An In-depth Evaluation of an Optimized Algorithm for DNA Motive Discovery. Int. J. Syst. Sci. Appl. Math. 2019, 3(4), 67-73. doi: 10.11648/j.ijssam.20180304.11

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    AMA Style

    Amannah Constance Izuchukwu, Ernest Chukwuka Ukwosah. An In-depth Evaluation of an Optimized Algorithm for DNA Motive Discovery. Int J Syst Sci Appl Math. 2019;3(4):67-73. doi: 10.11648/j.ijssam.20180304.11

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  • @article{10.11648/j.ijssam.20180304.11,
      author = {Amannah Constance Izuchukwu and Ernest Chukwuka Ukwosah},
      title = {An In-depth Evaluation of an Optimized Algorithm for DNA Motive Discovery},
      journal = {International Journal of Systems Science and Applied Mathematics},
      volume = {3},
      number = {4},
      pages = {67-73},
      doi = {10.11648/j.ijssam.20180304.11},
      url = {https://doi.org/10.11648/j.ijssam.20180304.11},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ijssam.20180304.11},
      abstract = {Motive Finding is the process of locating the meaningful patterns in the sequence of DNA, RNA or Proteins. There are many widely used algorithms in practice to solve the motive finding problem and these methods are local search methods. Different search algorithms were discussed which are Gibbs sampling, projection, pattern branching, and profile branching. The limitations surrounding them gave an advantage for the selection of the best algorithm in producing an optimized algorithm for the DNA discovery.},
     year = {2019}
    }
    

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    AB  - Motive Finding is the process of locating the meaningful patterns in the sequence of DNA, RNA or Proteins. There are many widely used algorithms in practice to solve the motive finding problem and these methods are local search methods. Different search algorithms were discussed which are Gibbs sampling, projection, pattern branching, and profile branching. The limitations surrounding them gave an advantage for the selection of the best algorithm in producing an optimized algorithm for the DNA discovery.
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Author Information
  • Department of Computer Science, Ignatius Ajuru University of Education, Port Harcourt, Nigeria

  • Department of Computer Science, Federal University, Wukari, Nigeria

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