Alignment of RNA base pairing probability matrices.
BACKGROUND
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.


BACKGROUND
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
Hofacker
Ivo L
IL
Institut für Theoretische Chemie und Molekulare Strukturbiologie, Universität Wien, Währingerstrasse 17, Vienna, Austria. ivo@tbi.univie.ac.at
Bernhart
Stephan H F
SH
Stadler
Peter F
PF
D000465:Algorithms; D020029:Base Pairing; D001483:Base Sequence; D017124:Conserved Sequence; D008956:Models, Chemical; D008957:Models, Genetic; D015233:Models, Statistical; D008969:Molecular Sequence Data; D012313:RNA / Q000737:chemistry* / Q000235:genetics*; D016415:Sequence Alignment / Q000379:methods*; D017423:Sequence Analysis, RNA / Q000379:methods*; D012689:Sequence Homology, Nucleic Acid
D012313:RNA