Article

# Alignment of RNA base pairing probability matrices.

Institut für Theoretische Chemie und Molekulare Strukturbiologie, Universität Wien, Währingerstrasse 17, Vienna, Austria.

Bioinformatics (Impact Factor: 5.32). 10/2004; 20(14):2222-7. DOI: 10.1093/bioinformatics/bth229 Source: PubMed

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**ABSTRACT:**The current pairwise RNA (secondary) structural alignment algorithms are based on Sankoff's dynamic programming algorithm from 1985. Sankoff's algorithm requires O(N(6)) time and O(N(4)) space, where N denotes the length of the compared sequences, and thus its applicability is very limited. The current literature offers many heuristics for speeding up Sankoff's alignment process, some making restrictive assumptions on the length or the shape of the RNA substructures. We show how to speed up Sankoff's algorithm in practice via non-heuristic methods, without compromising optimality. Our analysis shows that the expected time complexity of the new algorithm is O(N(4)sigma(N)), where sigma(N) converges to O(N), assuming a standard polymer folding model which was supported by experimental analysis. Hence, our algorithm speeds up Sankoff's algorithm by a linear factor on average. In simulations, our algorithm speeds up computation by a factor of 3-12 for sequences of length 25-250. Code and data sets are available, upon request.Journal of computational biology: a journal of computational molecular cell biology 08/2010; 17(8):1051-65. · 1.69 Impact Factor - [Show abstract] [Hide abstract]

**ABSTRACT:**MOTIVATION: The calculation of reliable alignments for structured RNA is still considered as an open problem. One approach is the incorporation of secondary structure information into the optimisation criteria by using a weighted sum of sequence and structure components as an objective function. Since it is not clear how to choose the weighting parameters, we use multi-objective optimisation to calculate a set of Pareto-optimal RNA sequence- structure alignments. The solutions in this set then represent all possible trade-offs between the different objectives, independent of any prior weighting. RESULTS: We present a practical multi-objective dynamic programming algorithm which is a new method for the calculation of the set of Pareto-optimal solutions to the pairwise RNA sequence-structure alignment problem. In selected examples, we show the usefulness of this approach, and its advantages over state-of-the-art single- objective algorithms. AVAILABILITY: The source code of our software (ISO C++11) is freely available at http://sysbio.uni-ulm.de/?Software and is licensed under the GNU GPLv3. CONTACT: hans.kestler@uni-ulm.de SUPPLEMENTARY INFORMATION: Suppelementary data are available at Bioinformatics online.Bioinformatics 04/2013; · 5.47 Impact Factor -
##### Conference Paper: SPARSE: quadratic time simultaneous alignment and folding of RNAs without sequence-based heuristics

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**ABSTRACT:**Motivation: There is increasing evidence of pervasive transcription, resulting in hundreds of thousands of ncRNAs of unknown function. Standard computational analysis tasks for inferring functional annotations like clustering require fast and accurate RNA comparisons based on sequence and structure similarity. The gold standard for the latter is Sankoff's algorithm [3], which simultaneously aligns and folds RNAs. Because of its extreme time complexity of O(n6), numerous faster "Sankoff-style" approaches have been suggested. Several such approaches introduce heuristics based on sequence alignment, which compromises the alignment quality for RNAs with sequence identities below 60% [1]. Avoiding such heuristics, as e.g. in LocARNA [4], has been assumed to prohibit time complexities better than O(n4), which strongly limits large-scale applications.Proceedings of the 17th international conference on Research in Computational Molecular Biology; 04/2013

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