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Detecting periodic patterns in biological sequences

E Coward1, F Drabløs

  • 1Department of Mathematical Sciences, Norwegian University of Science and Technology, Norway. evindc@math.ntnu.no

Bioinformatics (Oxford, England)
|August 8, 1998
PubMed
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A new method identifies periodic patterns in DNA and protein sequences using evolutionary distance and phase shifts. This approach efficiently detects sequence repeats, crucial for modern bioinformatics and genome analysis.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Sequence Analysis

Background:

  • Identifying repeated patterns in biological sequences is vital for sequence analysis.
  • Large-scale genome projects necessitate sensitive, automated methods for repeat detection.

Purpose of the Study:

  • To present a novel method for discovering periodic patterns in biological sequences.
  • To develop an efficient algorithm for identifying repeats in DNA and protein sequences.

Main Methods:

  • The method utilizes evolutionary distance and 'phase shifts' to account for insertions and deletions.
  • Sequences are aligned to themselves to minimize distance to periodicity, employing an iterative algorithm.
  • A 'phase score' is introduced to statistically assess the significance of detected periodicity.

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Main Results:

  • The algorithm achieves near-linear running time relative to sequence length.
  • A periodic consensus pattern is generated through sequence alignment.
  • The method successfully identified patterns in example DNA and protein sequences.

Conclusions:

  • The developed method offers a sensitive and efficient approach for detecting periodic patterns in biological sequences.
  • This technique is applicable to both DNA and protein sequence analysis, aiding in understanding sequence organization and function.