Volume 6 Number 3 (Mar. 2011)
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JSW 2011 Vol.6(3): 386-394
doi: 10.4304/jsw.6.3.386-394

A New Model for Finding Approximate Tandem Repeats in DNA Sequences

Qingshan Jiang 1,2 , Sheng Li 2 , Shun Guo 3 , Dan Wei 4

  • 1 Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China
  • 2 Software School, Xiamen University, Xiamen, China
  • 3 School of Information Science and Technology, Xiamen University, Xiamen, China
  • 4 Cognitive Science Department, Xiamen University, Xiamen, China; Fujian Key Laboratory of the Brain-like Intelligent Systems (Xiamen University), Xiamen, China

Abstract

In gene analysis, finding approximate tandem repeats in DNA sequence is an important issue. SUA_SATR is one of the latest methods for finding those repetitions, which suffers deficiencies of runtime cost and poor result quality. In order to detect approximate tandem repeats in genomic sequences more efficiently, we propose a new model based on a novel algorithm MSATR and an optimized algorithm <em>m</em>MSATR in this paper. The model uses the Motif-Divide method to improve the performance, which results in the proposal of algorithm MSATR. By introducing the definition of CASM to reduce the searching scope and optimizing the original mechanism adopted by MSATR, the <em>m</em>MSATR algorithm makes the detecting process more efficient and improves the result quality. The theoretical analysis and experiment results indicate that MSATR and <em>m</em>MSATR is able to get more results within less runtime. These algorithms are superior to other methods in finding results, and it greatly reduces the runtime cost, which is of benefit when the gene data becomes larger.

Keywords

  • DNA
  • sequence
  • mining;
  • approximate
  • tandem
jsw0603-6

How to Cite

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Qingshan Jiang, Sheng Li, Shun Guo, and Dan Wei, "A New Model for Finding Approximate Tandem Repeats in DNA Sequences," Journal of Software, vol. 6, no. 3, pp. 386-394, 2011. https://doi.org/ 10.4304/jsw.6.3.386-394

Copyright & License

Copyright © 2011 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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General Information

  • ISSN: 1796-217X (Online)

  • Abbreviated Title: J. Softw.

  • Frequency:  Biannually

  • APC: 500USD

  • DOI: 10.17706/JSW

  • Editor-in-Chief: Prof. Antanas Verikas

  • Executive Editor: Ms. Cecilia Xie

  • Abstracting/ Indexing: DBLP, CNKI, 

  • Google Scholar, ProQuest,
           INSPEC(IET), ULRICH's Periodicals
           Directory, WorldCat, etc

  • E-mail: editor@jsoftware.us

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