Bioinformatics, 22(14):1723-1729, May 2006 (article)
The functions of non-coding RNAs
are strongly related to their secondary structures,
but it is known
that a secondary structure prediction of a single sequence is not reliable.
Therefore, we have to collect similar RNA sequences
with a common secondary structure
for the analyses of a new non-coding RNA
without knowing the exact secondary structure itself.
Therefore, the sequence comparison in searching similar RNAs should consider
not only their sequence similarities but their potential secondary structures.
Sankoff&lsquo;s algorithm predicts the common secondary structures of the sequences,
but it is computationally too expensive to apply to large-scale analyses.
Because we often want to compare a large number of cDNA sequences
or to search similar RNAs in the whole genome sequences,
much faster algorithms are required.
We propose a new method of comparing RNA sequences
based on the structural alignments
of the fixed-length fragments of the stem candidates.
The implemented software,
SCARNA (Stem Candidate Aligner for RNAs),
is fast enough to apply to the long sequences
in the large-scale analyses.
The accuracy of the alignments is better or comparable
to the much slower existing algorithms.
Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems