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RAGA: RNA sequence alignment by genetic algorithm

C Notredame1, E A O'Brien, D G Higgins

  • 1EMBL Outstation-The European Bioinformatics Institute, Welcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. cedric.notredame@ebi.ac.uk

Nucleic Acids Research
|February 12, 1998
PubMed
Summary
This summary is machine-generated.

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We developed RAGA and PRAGA software using genetic algorithms for accurate RNA sequence alignment. These tools optimize alignments by considering both primary and secondary RNA structures, including complex pseudoknots.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Molecular Biology

Background:

  • Accurate alignment of homologous RNA sequences is crucial for understanding RNA function and evolution.
  • Existing methods may not fully account for RNA secondary structures, including pseudoknots, which can impact alignment accuracy.

Purpose of the Study:

  • To present a novel computational approach for precise pairwise RNA sequence alignment.
  • To introduce two software packages, RAGA and PRAGA, that leverage genetic algorithms for optimizing RNA alignments.

Main Methods:

  • Development of RAGA, an extension of the SAGA multiple protein sequence alignment package.
  • Implementation of PRAGA, utilizing parallel genetic algorithms to optimize RNA pairwise alignments.
  • Optimization of an objective function incorporating primary and secondary RNA structures, including pseudoknots.

Related Experiment Videos

Main Results:

  • Demonstrated the capability of PRAGA to optimize RNA alignments considering both primary and secondary structures.
  • Successfully applied PRAGA to nine test cases involving eukaryotic small subunit rRNA sequences (nuclear and mitochondrial).

Conclusions:

  • RAGA and PRAGA offer a robust method for accurate RNA sequence alignment, especially when secondary structure information is available.
  • The genetic algorithm approach effectively handles complex RNA structures like pseudoknots, improving alignment quality.