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Alignment of possible secondary structures in multiple RNA sequences using simulated annealing
1Department of Computer Science, Michigan State University, East Lansing 48824, USA. kimj@cps
Computer Applications in the Biosciences : CABIOS
|August 1, 1996
Summary
This study presents a new algorithm for multiple RNA sequence alignment to identify common secondary structures. The method uses dot matrices and simulated annealing, improving efficiency and convergence for RNA structure prediction.
Area of Science:
- Bioinformatics
- Computational Biology
- Molecular Biology
Background:
- Multiple sequence alignment is crucial for identifying conserved RNA secondary structures.
- Existing methods may face computational challenges with increasing sequence numbers and lengths.
Purpose of the Study:
- To present a novel algorithm for multiple RNA sequence alignment.
- To identify possible common secondary structures in RNA sequences efficiently.
Main Methods:
- Utilizes dot matrices from intra-sequence comparisons to derive common secondary structures.
- Employs a score function based on hit probability and simulated annealing for optimization.
- Introduces strategies to reduce computation time and enhance convergence, including the 'double shuffle' transition rule.
Main Results:
- The algorithm effectively identifies potential common secondary structures in RNA sequences.
- Analysis of the solution set reveals effects of alignment gaps and length.
- Optimized strategies significantly reduce computation time and increase convergence rate.
Conclusions:
- The developed algorithm offers an efficient approach for RNA secondary structure prediction.
- The integration of dot matrices, simulated annealing, and optimized strategies enhances the accuracy and speed of alignment.
- This method advances the field of computational RNA structure analysis.