Improving RNA Structure Prediction with Pairwise Alignment
Author Information
Author(s): Robin D. Dowell, Sean R. Eddy
Primary Institution: Howard Hughes Medical Institute and Department of Genetics, Washington University School of Medicine
Hypothesis
Can incorporating sequence alignment constraints improve RNA secondary structure prediction accuracy?
Conclusion
Pairwise RNA structural alignment improves on structure prediction accuracy relative to single sequence folding.
Supporting Evidence
- Pairwise RNA structural alignment improves prediction accuracy.
- Using alignment constraints reduces runtime and memory requirements.
- Five implementations of the pairwise Sankoff algorithm show comparable performance.
Takeaway
This study shows that using information from similar RNA sequences can help predict their shapes better and faster.
Methodology
The study developed a constrained version of the pairSCFG structural alignment algorithm using probabilistic models to score pairwise alignment and folding.
Limitations
The algorithm's performance may vary with the evolutionary divergence of RNA sequences.
Digital Object Identifier (DOI)
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