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Alignments without low-scoring regions

Z Zhang1, P Berman, W Miller

  • 1Department of Computer Science and Engineering, The Pennsylvania State University, University Park 16802, USA.

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|July 22, 1998
PubMed
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This study explores extending sequence alignments with gaps, focusing on efficiently finding meaningful extensions. Algorithms provide less rigorous conditions for practical sequence database searching, as implemented in Blast.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Sequence Analysis

Background:

  • Extending sequence alignments with gaps is crucial for biological sequence analysis.
  • Current methods may be computationally expensive when searching for meaningful alignment extensions.

Purpose of the Study:

  • To develop efficient algorithms for extending sequence alignments with gaps.
  • To avoid searching beyond regions likely to yield useful alignment extensions.

Main Methods:

  • Formalizing the problem as aligning sequence portions with a minimum score constraint (-X).
  • Investigating the computational cost of optimal alignments under this constraint.
  • Developing efficient algorithms for less rigorous alignment conditions.

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Main Results:

  • Computing an optimal alignment under the specified constraint is computationally expensive.
  • Efficient algorithms can guarantee less rigorous conditions for sequence alignment.
  • A variant algorithm has been implemented in the Blast suite.

Conclusions:

  • Efficient algorithms offer a practical approach to extending sequence alignments with gaps.
  • The implemented variant enhances the capabilities of database search programs like Blast.