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Normalization of affine gap costs used in optimal sequence alignment

L Allison1

  • 1Department of Computer Science, Monash University, Australia.

Journal of Theoretical Biology
|March 21, 1993
PubMed
Summary

This study introduces a method to normalize alignment algorithm costs. Normalized costs reveal explicit models linking sequence data to mutation and evolution processes.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Evolutionary Biology

Background:

  • Sequence alignment algorithms are crucial for comparing biological sequences.
  • Affine and linear gap costs are commonly used in alignment.
  • Interpreting alignment costs in a probabilistic framework is challenging.

Purpose of the Study:

  • To normalize costs in sequence alignment algorithms using affine or linear gap costs.
  • To establish an explicit model connecting sequence alignment to biological processes.
  • To provide a probabilistic interpretation of alignment costs.

Main Methods:

  • Developing a normalization technique for alignment algorithm costs.
  • Interpreting normalized costs as -log probabilities.
  • Utilizing finite-state edit-machines to model sequence relationships.

Main Results:

  • A method for normalizing alignment costs is presented.
  • Normalized costs are shown to represent -log probabilities of edit-machine instructions.
  • An explicit model linking sequence data to mutation and evolution is derived.

Conclusions:

  • The normalization method provides a probabilistic interpretation of sequence alignment.
  • The derived model offers insights into mutation and evolutionary processes.
  • This work bridges sequence alignment algorithms with evolutionary modeling.

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