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A search for common patterns in many sequences.

M A Roytberg1

  • 1Research Computer Center, Pushchino, Moscow Region, USSR.

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|February 1, 1992
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Summary
This summary is machine-generated.

This study introduces a novel algorithm for finding common patterns across multiple sequences, even with variations like substitutions and insertions. The method efficiently identifies similar segments in biological sequences, regardless of their position or degree of similarity.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Sequence Analysis

Background:

  • Identifying common patterns in biological sequences is crucial for understanding molecular function and evolution.
  • Existing methods may struggle with variations in sequence similarity, position, and length.

Purpose of the Study:

  • To present a new, efficient algorithm for detecting common patterns in multiple sequences.
  • To enable the identification of similar segments despite differences in substitutions, insertions, and deletions.

Main Methods:

  • A novel approach using a 'basic' sequence to find similarities across a set of sequences.
  • Reconstruction of multiple similarities from pairwise comparisons.
  • Algorithm complexity is O(n*L^2) for n sequences of length L.

Main Results:

  • The algorithm successfully identifies similar segments present in all or a majority of sequences.
  • It accommodates variations in sequence content, including substitutions and indels (insertions/deletions).
  • Demonstrated applicability to biopolymer primary structure analysis.

Conclusions:

  • The proposed algorithm offers a flexible and efficient method for common pattern discovery in sequence data.
  • It is effective for analyzing biological sequences where similarity may be fragmented or non-contiguous.
  • The choice of the basic sequence can influence the results, highlighting an area for further investigation.