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Computing Nonoverlapping Inversion Distance Between Two Strings in Linear Average Time.

Xiaodong Wang1, Lei Wang2

  • 11 Computer Science Department, Fujian University of Technology, Fuzhou, China.

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|January 15, 2019
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Summary

This study introduces a novel algorithm for calculating inversion distance between biological sequences. The new method achieves linear average time and linear space complexity, significantly improving upon previous quadratic space requirements.

Keywords:
algorithmscombinatoricsoptimization

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Standard alignment algorithms do not detect biological inversions.
  • The inversion distance problem is computationally complex, with previous algorithms having high time and space complexities.

Purpose of the Study:

  • To develop a more efficient algorithm for computing inversion distance between two strings.
  • To reduce the computational resources required for inversion distance calculations.

Main Methods:

  • A new recursive formula was developed for calculating inversion distance.
  • The algorithm was designed for linear average time and linear space complexity.

Main Results:

  • The proposed algorithm achieves linear average time complexity.
  • The algorithm utilizes linear space complexity, a significant improvement over existing quadratic space methods.

Conclusions:

  • This work presents the first linear space and linear average time algorithm for the inversion distance problem.
  • The novel recursive formula offers a breakthrough in efficient computation of biological sequence inversions.