Alignment of RNA base pairing probability matrices.

Ivo L Hofacker; Stephan H F Bernhart; Peter F Stadler

doi:10.1093/bioinformatics/bth229

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PubMed · 15073017

Alignment of RNA base pairing probability matrices.

Ivo L Hofacker·Stephan H F Bernhart·Peter F Stadler

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Abstract

MOTIVATION: Many classes of functional RNA molecules are characterized by highly conserved secondary structures but little detectable sequence similarity. Reliable multiple alignments can therefore be constructed only when the shared structural features are taken into account. Since multiple alignments are used as input for many subsequent methods of data analysis, structure-based alignments are an indispensable necessity in RNA bioinformatics. RESULTS: We present here a method to compute pairwise and progressive multiple alignments from the direct comparison of base pairing probability matrices. Instead of attempting to solve the folding and the alignment problem simultaneously as in the classical Sankoff's algorithm, we use McCaskill's approach to compute base pairing probability matrices which effectively incorporate the information on the energetics of each sequences. A novel, simplified variant of Sankoff's algorithms can then be employed to extract the maximum-weight common secondary structure and an associated alignment. AVAILABILITY: The programs pmcomp and pmmulti described in this contribution are implemented in Perl and can be downloaded together with the example datasets from http://www.tbi.univie.ac.at/RNA/PMcomp/. A web server is available at http://rna.tbi.univie.ac.at/cgi-bin/pmcgi.pl

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Algorithms Base Pairing Base Sequence Conserved Sequence Models, Chemical Models, Genetic Models, Statistical Molecular Sequence Data RNA Sequence Alignment Sequence Analysis, RNA Sequence Homology, Nucleic Acid Comparative Study Evaluation Study Journal Article Research Support, Non-U.S. Gov't Validation Study

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Ivo L Hofacker, Stephan H F Bernhart, Peter F Stadler. 2004-04-08. Alignment of RNA base pairing probability matrices.. https://doi.org/10.1093/bioinformatics%2Fbth229

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