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The ITS2 Database
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Published on: March 12, 2012

The tree alignment problem.

Andrés Varón1, Ward C Wheeler

  • 1Division of Invertebrate Zoology, American Museum of Natural History, New York, NY 10024, USA.

BMC Bioinformatics
|November 13, 2012
PubMed
Summary
This summary is machine-generated.

A new algorithm, Affine-DO, improves multiple sequence alignment for phylogenetic analysis. It offers scalability and near-optimal solutions for DNA sequence homology inference, enhancing evolutionary studies.

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Evolutionary Biology

Background:

  • Inferring DNA sequence homology is vital for understanding evolution but computationally challenging.
  • The multiple sequence alignment problem and its tree alignment variant are key computational tasks.
  • Existing methods like Direct Optimization (DO) offer speed but may not optimally handle alignment gap models.

Purpose of the Study:

  • Introduce Affine-DO, a novel algorithm for multiple sequence alignment.
  • Accommodate affine gap models crucial for phylogenetic analysis of molecular sequences.
  • Evaluate Affine-DO's performance and scalability against established methods.

Main Methods:

  • Developed the Affine-DO algorithm, building upon the Direct Optimization (DO) heuristic.
  • Implemented Affine-DO and conducted extensive experimental testing (>330,000 trials).
  • Compared Affine-DO's solutions to lower bounds derived from linear programming.

Main Results:

  • Affine-DO demonstrates comparable time complexity to DO but is optimized for affine gap models.
  • Experimental results show Affine-DO solutions approximate linear programming lower bounds.
  • Iterative refinement of Affine-DO solutions yielded minimal improvements, suggesting high-quality outputs.

Conclusions:

  • Affine-DO provides near-optimal solutions for multiple sequence alignment in phylogenetics.
  • Approximation accuracy is within 10% for low-divergence sequences and 30% for random sequences.
  • Affine-DO offers significant improvements in scalability and optimality for phylogenetic sequence analysis.