Complete probabilistic analysis of RNA shapes

Voß B, Giegerich R, Rehmsmeier M (2006)
BMC Biology 4(1): 5.

Journal Article | Published | English
Background: Soon after the first algorithms for RNA folding became available, it was recognised that the prediction of only one energetically optimal structure is insufficient to achieve reliable results. An in-depth analysis of the folding space as a whole appeared necessary to deduce the structural properties of a given RNA molecule reliably. Folding space analysis comprises various methods such as suboptimal folding, computation of base pair probabilities, sampling procedures and abstract shape analysis. Common to many approaches is the idea of partitioning the folding space into classes of structures, for which certain properties can be derived. Results: In this paper we extend the approach of abstract shape analysis. We show how to compute the accumulated probabilities of all structures that share the same shape. While this implies a complete (non-heuristic) analysis of the folding space, the computational effort depends only on the size of the shape space, which is much smaller. This approach has been integrated into the tool RNAshapes, and we apply it to various RNAs. Conclusion: Analyses of conformational switches show the existence of two shapes with probabilities approximately 2/3 vs. 1/3, whereas the analysis of a microRNA precursor reveals one shape with a probability near to 1.0. Furthermore, it is shown that a shape can outperform an energetically more favourable one by achieving a higher probability. From these results, and the fact that we use a complete and exact analysis of the folding space, we conclude that this approach opens up new and promising routes for investigating and understanding RNA secondary structure.
Publishing Year

Cite this

Voß B, Giegerich R, Rehmsmeier M. Complete probabilistic analysis of RNA shapes. BMC Biology. 2006;4(1):5.
Voß, B., Giegerich, R., & Rehmsmeier, M. (2006). Complete probabilistic analysis of RNA shapes. BMC Biology, 4(1), 5. doi:10.1186/1741-7007-4-5
Voß, B., Giegerich, R., and Rehmsmeier, M. (2006). Complete probabilistic analysis of RNA shapes. BMC Biology 4, 5.
Voß, B., Giegerich, R., & Rehmsmeier, M., 2006. Complete probabilistic analysis of RNA shapes. BMC Biology, 4(1), p 5.
B. Voß, R. Giegerich, and M. Rehmsmeier, “Complete probabilistic analysis of RNA shapes”, BMC Biology, vol. 4, 2006, pp. 5.
Voß, B., Giegerich, R., Rehmsmeier, M.: Complete probabilistic analysis of RNA shapes. BMC Biology. 4, 5 (2006).
Voß, Björn, Giegerich, Robert, and Rehmsmeier, Marc. “Complete probabilistic analysis of RNA shapes”. BMC Biology 4.1 (2006): 5.
All files available under the following license(s):
Copyright Statement:
This Item is protected by copyright and/or related rights. [...]
Main File(s)
Access Level
OA Open Access

This data publication is cited in the following publications:
This publication cites the following data publications:

34 Citations in Europe PMC

Data provided by Europe PubMed Central.

RNArchitecture: a database and a classification system of RNA families, with a focus on structural information.
Boccaletto P, Magnus M, Almeida C, Zyla A, Astha A, Pluta R, Baginski B, Jankowska E, Dunin-Horkawicz S, Wirecki TK, Boniecki MJ, Stefaniak F, Bujnicki JM., Nucleic Acids Res. 46(D1), 2018
PMID: 29069520
Compound Image Segmentation of Published Biomedical Figures.
Li P, Jiang X, Kambhamettu C, Shatkay H., Bioinformatics (), 2017
PMID: 29040394
The BRaliBase dent-a tale of benchmark design and interpretation.
Lowes B, Chauve C, Ponty Y, Giegerich R., Brief. Bioinformatics 18(2), 2017
PMID: 26984616
Algebraic Dynamic Programming over general data structures.
zu Siederdissen CH, Prohaska SJ, Stadler PF., BMC Bioinformatics 16 Suppl 19(), 2015
PMID: 26695390
Pareto optimization in algebraic dynamic programming.
Saule C, Giegerich R., Algorithms Mol Biol 10(), 2015
PMID: 26150892
Fighting against uncertainty: an essential issue in bioinformatics.
Hamada M., Brief. Bioinformatics 15(5), 2014
PMID: 23803300
A silent exonic SNP in kdm3a affects nucleic acids structure but does not regulate experimental autoimmune encephalomyelitis.
Gillett A, Bergman P, Parsa R, Bremges A, Giegerich R, Jagodic M., PLoS ONE 8(12), 2013
PMID: 24312603
Shape and secondary structure prediction for ncRNAs including pseudoknots based on linear SVM.
Achawanantakun R, Sun Y., BMC Bioinformatics 14 Suppl 2(), 2013
PMID: 23369147

33 References

Data provided by Europe PubMed Central.

Le S, Chen J, Maizel J., 1990
Structural RNA has lower folding energy than random RNA of the same dinucleotide frequency.
Clote P, Ferre F, Kranakis E, Krizanc D., RNA 11(5), 2005
PMID: 15840812

Bellmann R., 1957
RNAshapes: an integrated RNA analysis package based on abstract shapes.
Steffen P, Voss B, Rehmsmeier M, Reeder J, Giegerich R., Bioinformatics 22(4), 2006
PMID: 16357029


0 Marked Publications

Open Data PUB

Web of Science

View record in Web of Science®


PMID: 16480488
PubMed | Europe PMC

Search this title in

Google Scholar