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(n2)], 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.#R##N##R##N#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.#R##N##R##N#Availability and implementation: Source code (C and perl) and binaries for linux are freely available at www.zbh.uni-hamburg.de/fries.#R##N##R##N#Contact: tim.wiegels@gmail.com
['Tim Wiegels', 'Stefan Bienert', 'Andrew E. Torda']
Fast alignment and comparison of RNA structures