The Journal of the Convergence on Culture Technology (문화기술의 융합)

The International Promotion Agency of Culture Technology (국제문화기술진흥원)
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Implementation and Application of Multiple Local Alignment

다중 지역 정렬 알고리즘 구현 및 응용

  • 이계성 (단국대학교 소프트웨어학과)
  • Received : 2019.06.02
  • Accepted : 2019.07.12
  • Published : 2019.08.31
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Abstract

Global sequence alignment in search of similarity or homology favors larger size of the sequence because it keeps looking for more similar section between two sequences in the hope that it adds up scores for matched part in the rest of the sequence. If a substantial size of mismatched section exists in the middle of the sequence, it greatly reduces the total alignment score. In this case a whole sequence would be better to be divided into multiple sections. Overall alignment score over the multiple sections of the sequence would increase as compared to global alignment. This method is called multiple local alignment. In this paper, we implement a multiple local alignment algorithm, an extension of Smith-Waterman algorithm and show the experimental results for the algorithm that is able to search for sub-optimal sequence.

서열 정렬에 있어서 전체를 비교하여 두 서열 사이의 최대의 유사성 또는 상동성을 찾는 전역 정렬은 넓은 범위를 선호하게 되는 편향성을 갖게 된다. 비일치 부분을 과감히 제거하고 높은 일치도를 갖는 부분 영역을 정렬하게 되면 정렬점수를 높이는 효과를 갖게 된다. 여러 개의 부분 지역 정렬을 탐색하게 하는 다중 지역정렬 방법을 적용하여 다수의 지역정렬을 수행하는 알고리즘을 구현하고 결과를 분석해 본다. 지역 정렬에 일반적으로 사용되는 Smith-Waterman 알고리즘의 제한점 중 하나인 서열이 길어지는 것을 방지하고, sub-optimal sequence를 찾기 위한 방법을 응용하여 다중지역 정렬을 수행한다.

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References

  1. J. Momand, A. McCurdy and S. Heubach, "Concepts in Bioinformatics and Genomics," Oxford, 2017.
  2. M.A. Schaib, I.M. Kaplow, M. Sirata, and S. Batzaglau, "A Classifier based approach to identify genetic similarity between diseases," 2009.
  3. C.B. Abhilash and K. Rohitaksha, "A Comparative Study on Global and Local Alignment Algorithms Methods," Int. Journal of Emerging Tech. and Adv. Engineering, Vol. 4, Issue 1, pp. 34-43, Jan 2014.
  4. Z. Zhang, P. Berman, T. Wiehe, and W. Miller "Post-processing long pairwise alignments" Bioinformatics, Vol. 15, pp. 1012-1019, 1999. https://doi.org/10.1093/bioinformatics/15.12.1012
  5. A.N. Arslan, O. Egecioglu, and and P.A. Pevzner "A new approach to sequence comparison: Normalized sequence alignment" Bioinformatics, Vol.17(4) pp.327-337, 2001. https://doi.org/10.1093/bioinformatics/17.4.327
  6. A.N. Arslan and O. Egecioglu, "Algorithms for Local Alignments with Length Constraints", Proc. 5th Latin American Theoretical Informatics Symposium, Lecture Notes in Computer Science 2286, pp. 38-51, April 2002.
  7. M. Hess, F. Keul, M. Goesele and K. Hamacher, "Addressing inaccuracies in BLOSUM computation improves homology search performance," BMC Bioinformatics Vol.17, 2016.
  8. https://en.wikipedia.org/wiki/Point_accepted_mutation