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An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

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Published on: July 12, 2022

Multiperm: shuffling multiple sequence alignments while approximately preserving dinucleotide frequencies.

Parvez Anandam1, Elfar Torarinsson, Walter L Ruzzo

  • 1Department of Computer Science and Engineering, University of Washington, Seattle, WA 98195-2350, USA. anandam@u.washington.edu

Bioinformatics (Oxford, England)
|January 13, 2009
PubMed
Summary
This summary is machine-generated.

A new algorithm, Multiperm, shuffles multiple sequence alignments to create a null model for RNA structure prediction. This method preserves key sequence features, improving statistical significance assessments for RNA structure.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Structural Biology

Background:

  • Assessing statistical significance of RNA structures from multiple sequence alignments requires a robust null model.
  • Existing shuffling algorithms do not adequately preserve crucial characteristics of multiple sequence alignments.

Purpose of the Study:

  • To introduce Multiperm, a novel random shuffling algorithm for multiple sequence alignments.
  • To provide a better null model for evaluating the statistical significance of predicted RNA structures.

Main Methods:

  • Developed Multiperm, a C++ source code algorithm.
  • Multiperm preserves gap structure, local conservation, and approximate dinucleotide frequencies in alignments.
  • Applied Multiperm to shuffle exonic sequences.

Main Results:

  • Multiperm successfully preserves gap and local conservation structure, along with dinucleotide frequencies.
  • Shuffled sequences generated by Multiperm exhibit folding free energy closer to native sequences compared to other methods.
  • Demonstrates the effectiveness of Multiperm as a null model for RNA structure prediction.

Conclusions:

  • Multiperm offers a significant advancement in creating null models for statistical assessment of RNA structures.
  • The algorithm's ability to preserve multiple sequence alignment features enhances the reliability of RNA structure predictions.
  • Availability of Multiperm source code facilitates its use in the research community.