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Reconstruction of strings past

C N Yee1, L Allison

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

Computer Applications in the Biosciences : CABIOS
|February 1, 1993
PubMed
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This study introduces a novel string-alignment method using minimum message length encoding to accurately estimate evolutionary parameters. This approach outperforms traditional single optimal alignment methods in recovering evolutionary history.

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Evolutionary Biology

Background:

  • String-alignment algorithms are crucial for comparing macromolecules to infer evolutionary relationships.
  • Estimating evolutionary divergence and common ancestry relies on accurate sequence alignment.

Purpose of the Study:

  • To apply minimum message length (MML) encoding to the string-alignment problem.
  • To develop a novel alignment method that averages over all possible alignments.

Main Methods:

  • Utilized minimum message length encoding, a principle of inductive inference.
  • Developed a weighted averaging approach across multiple sequence alignments.

Main Results:

  • The MML-based alignment method accurately recovers evolutionary parameters across a wide range of values.

Related Experiment Videos

  • This novel method demonstrates higher accuracy compared to using a single optimal alignment.

    • Conclusions:

    • Minimum message length encoding provides a robust framework for sequence alignment in evolutionary studies.
    • Averaging over alignments using MML yields less biased and more accurate estimations of evolutionary history.