Partition function and base pairing probabilities for RNA–RNA interaction prediction

Motivation: The RNA–RNA interaction problem (RIP) consists in finding the energetically optimal structure of two RNA molecules that bind to each other. The standard model allows secondary structures in both partners as well as additional base pairs between the two RNAs subject to certain restriction...

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Veröffentlicht in:Bioinformatics Jg. 25; H. 20; S. 2646 - 2654
Hauptverfasser: Huang, Fenix W. D., Qin, Jing, Reidys, Christian M., Stadler, Peter F.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford Oxford University Press 15.10.2009
Schlagworte:
Algorithms
Base Pairing
Biological and medical sciences
Computational Biology - methods
Databases, Genetic
Fundamental and applied biological sciences. Psychology
General aspects
Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)
Nucleic Acid Conformation
RNA - chemistry
RNA - metabolism
Thermodynamics
Partition
Partition function
RNA
Interaction
Prediction
Probability
Base pairing
ISSN:1367-4803, 1367-4811, 1460-2059, 1367-4811
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Zusammenfassung:Motivation: The RNA–RNA interaction problem (RIP) consists in finding the energetically optimal structure of two RNA molecules that bind to each other. The standard model allows secondary structures in both partners as well as additional base pairs between the two RNAs subject to certain restrictions that ensure that RIP is solvabale by a polynomial time dynamic programming algorithm. RNA–RNA binding, like RNA folding, is typically not dominated by the ground state structure. Instead, a large ensemble of alternative structures contributes to the interaction thermodynamics. Results: We present here an O(N6) time and O(N4) dynamics programming algorithm for computing the full partition function for RIP which is based on the combinatorial notion of ‘tight structures’. Albeit equivalent to recent work by H. Chitsaz and collaborators, our approach in addition provides a full-fledged computation of the base pairing probabilities, which relies on the notion of a decomposition tree for joint structures. In practise, our implementation is efficient enough to investigate, for instance, the interactions of small bacterial RNAs and their target mRNAs. Availability: The program rip is implemented in C. The source code is available for download from http://www.combinatorics.cn/cbpc/rip.html and http://www.bioinf.uni-leipzig.de/Software/rip.html. Contact: duck@santafe.edu Supplementary information: Supplementary data are available at Bioinformatics online.
Bibliographie:ArticleID:btp481
istex:C88077A326C7408C76A8949D01D1D374344A5896
To whom correspondence should be addressed.
Associate Editor: Ivo Hofacker
ark:/67375/HXZ-5PFMKBZT-Q
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ISSN:1367-4803
1367-4811
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btp481