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RNA Secondary Structure Prediction Using High-throughput SHAPE
13:42

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

Predicting consensus structures for RNA alignments via pseudo-energy minimization.

Junilda Spirollari1, Jason T L Wang, Kaizhong Zhang

  • 1Bioinformatics Program, Department of Computer Science, New Jersey Institute of Technology, University Heights, Newark, NJ 07102, U.S.A.

Bioinformatics and Biology Insights
|February 9, 2010
PubMed
Summary
This summary is machine-generated.

Predicting RNA secondary structures is improved using RSpredict, a new tool that analyzes multiple aligned RNA sequences. It leverages sequence covariation for higher accuracy in consensus secondary structure prediction.

Keywords:
Drosophila secondary structureRNA secondary structure predictionRfam sequence alignmentsnormalized energy

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Molecular Biology

Background:

  • RNA secondary structure prediction is crucial for understanding RNA function.
  • Existing methods using single sequences have moderate accuracy.
  • Incorporating covariance from multiple sequence alignments can improve predictions.

Purpose of the Study:

  • To develop a novel computational tool for predicting consensus RNA secondary structures from multiple sequence alignments.
  • To improve the accuracy of RNA secondary structure prediction by utilizing sequence covariation.

Main Methods:

  • Developed RSpredict, a tool employing pseudo-energy minimization and heuristics.
  • Input: Multiple sequence alignments (FASTA, ClustalW format).
  • Output: Consensus secondary structure (Vienna Dot Bracket, Connectivity Table formats).

Main Results:

  • RSpredict effectively incorporates sequence covariation for improved accuracy.
  • Performance was evaluated against established tools like KNetFold, Pfold, and RNAalifold.
  • Demonstrated competitive results on diverse datasets, including Rfam and Drosophila X chromosome alignments.

Conclusions:

  • RSpredict offers a competitive and accurate method for predicting consensus RNA secondary structures.
  • The tool effectively utilizes sequence covariation, outperforming single-sequence methods.
  • RSpredict is accessible as a web server and downloadable software.