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Bioinformatics Advance Access originally published online on November 15, 2007
Bioinformatics 2007 23(24):3304-3311; doi:10.1093/bioinformatics/btm525
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© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

MASTR: multiple alignment and structure prediction of non-coding RNAs using simulated annealing

Stinus Lindgreen 1,*, Paul P. Gardner 1,2,{dagger} and Anders Krogh 1

1Bioinformatics Centre and 2Molecular Evolution Group, Department of Molecular Biology, University of Copenhagen, Ole Maaloes Vej 5, 2200 Copenhagen N, Denmark

*To whom correspondence should be addressed.


  Abstract

Motivation: As more non–coding RNAs are discovered, the importance of methods for RNA analysis increases. Since the structure of ncRNA is intimately tied to the function of the molecule, programs for RNA structure prediction are necessary tools in this growing field of research. Furthermore, it is known that RNA structure is often evolutionarily more conserved than sequence. However, few existing methods are capable of simultaneously considering multiple sequence alignment and structure prediction.

Result: We present a novel solution to the problem of simultaneous structure prediction and multiple alignment of RNA sequences. Using Markov chain Monte Carlo in a simulated annealing framework, the algorithm MASTR (Multiple Alignment of STructural RNAs) iteratively improves both sequence alignment and structure prediction for a set of RNA sequences. This is done by minimizing a combined cost function that considers sequence conservation, covariation and basepairing probabilities. The results show that the method is very competitive to similar programs available today, both in terms of accuracy and computational efficiency.

Availability: Source code available from http://mastr.binf.ku.dk/

Contact: stinus{at}binf.ku.dk

Associate Editor: Dmitrij Frishman

{dagger}Present address: Wellcome Trust Sanger Institute, Cambridge, UK.

Received on August 20, 2007; revised on October 11, 2007; accepted on October 13, 2007

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