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Related Experiment Videos

A benchmark of multiple sequence alignment programs upon structural RNAs.

Paul P Gardner1, Andreas Wilm, Stefan Washietl

  • 1Department of Evolutionary Biology, University of Copenhagen Universitetsparken 15, 2100 Copenhagen Ø, Denmark. PPGardner@bi.ku.dk

Nucleic Acids Research
|April 30, 2005
PubMed
Summary
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Benchmarking nucleic acid sequence alignment algorithms reveals limitations. ProAlign and Clustal algorithms show better performance for structural RNA alignment, especially when sequence identity is low.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Molecular Biology

Background:

  • Protein alignment often uses sophisticated models (e.g., PAM, BLOSUM).
  • Nucleic acid sequence alignment lacks standardized, sophisticated models, often relying on ad hoc methods.
  • Benchmarking existing alignment algorithms for structural RNAs is underexplored.

Purpose of the Study:

  • To evaluate the applicability of common sequence alignment methods for structural RNA alignment.
  • To identify conditions where auxiliary information (e.g., secondary structure) is necessary.
  • To determine which sequence alignment algorithms perform best across diverse conditions.

Main Methods:

  • Systematic performance testing of existing sequence alignment algorithms.
  • Evaluation focused on structural RNA sequences.

Related Experiment Videos

  • Comparison of algorithm performance under varying conditions, including sequence identity thresholds.

    • Main Results:

    • Sequence alignment alone is generally inadequate for structural RNA alignment below 50-60% sequence identity.
    • Probabilistic method ProAlign and Clustal algorithms demonstrate superior performance compared to other sequence-based methods.
    • These top-performing algorithms are effective across a broad range of applications.

    Conclusions:

    • Current sequence alignment algorithms have limitations when applied to structural RNAs, particularly at lower sequence identities.
    • Researchers should consider incorporating secondary structure information to augment alignment.
    • ProAlign and Clustal represent more robust choices for structural RNA sequence alignment tasks.