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Article Abstract
Motivation: To recognize remote relationships between RNA molecules, one must be able to align structures without regard to sequence similarity. We have implemented a method, which is swift [O(n(2))], sensitive and tolerant of large gaps and insertions. Molecules are broken into overlapping fragments, which are characterized by their memberships in a probabilistic classification based on local geometry and H-bonding descriptors. This leads to a probabilistic similarity measure that is used in a conventional dynamic programming method.
Results: Examples are given of database searching, the detection of structural similarities, which would not be found using sequence based methods, and comparisons with a previously published approach.
Availability And Implementation: Source code (C and perl) and binaries for linux are freely available at www.zbh.uni-hamburg.de/fries.
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| http://dx.doi.org/10.1093/bioinformatics/btt006 | DOI Listing |
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