Thermodynamics of RNA–RNA binding

Mückstein, Ulrike; Tafer, Hakim; Hackermüller, Jörg; Bernhart, Stephan H.; Stadler, Peter F.; Hofacker, Ivo L.

doi:10.1093/bioinformatics/btl024

Cited by 339 publications

(291 citation statements)

References 45 publications

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“…On a set of several known RNA-RNA complexes, our proposed algorithm shows a reliable accuracy. Especially, This Table shows the sensitivity, PPV and F-measure for RNA-RNA binding sites prediction by (1) inRNAs, (2) IntaRNA [16], and (3) RNAup [15]. The dataset is compiled by Kato et al [13] and Busch et al [16].…”

Section: Discussionmentioning

confidence: 99%

“…One such method presented by Alkan et al [1], extends existing loop regions in independent structures to find potential binding sites. RNAup [15] presents an extension of the standard partition function approach to compute the probabilities that a sequence interval remains unpaired. IntaRNA [16] considers not only accessibility of a binding sites but also the existence of a seed to predict potential binding sites.…”

Section: Related Workmentioning

confidence: 99%

“…In order to identify the set of accessible regions in each sequence we set w = 25 and use E u < min{E u } + 2(kcal/mol) as cutoff. For assessing the predictive power of our algorithm, we compare our algorithm with IntaRNA [16] and RNAup [15]. Based on the experimental results presented by IntaRNA, both IntaRNA and RNAup which incorporate accessibility of target regions, perform better than the other competitive programs (TargetRNA [19], RNAhybrid [9], and RNAplex [20]).…”

Section: Binding Sites Predictionmentioning

confidence: 99%

See 2 more Smart Citations

Fast Prediction of RNA-RNA Interaction

Salari

Backofen

Şahinalp

2009

Lecture Notes in Computer Science

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Background: Regulatory antisense RNAs are a class of ncRNAs that regulate gene expression by prohibiting the translation of an mRNA by establishing stable interactions with a target sequence. There is great demand for efficient computational methods to predict the specific interaction between an ncRNA and its target mRNA(s). There are a number of algorithms in the literature which can predict a variety of such interactions -unfortunately at a very high computational cost. Although some existing target prediction approaches are much faster, they are specialized for interactions with a single binding site. Methods: In this paper we present a novel algorithm to accurately predict the minimum free energy structure of RNA-RNA interaction under the most general type of interactions studied in the literature. Moreover, we introduce a fast heuristic method to predict the specific (multiple) binding sites of two interacting RNAs.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Binding Sites Predictionmentioning

confidence: 99%

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Fast Prediction of RNA-RNA Interaction

Salari

Backofen

Şahinalp

2009

Lecture Notes in Computer Science

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“…(Penchovsky and Breaker, 2005). The second term we introduce is the intermolecular base pairing efficiency, (∆G int ) representing the disassociation of base pairs in the intramolecular binding region and formation of intermolecular base pairs calculated using the RNAup program Mückstein et al (2006). With these extension to Eq.…”

Section: G(x)mentioning

confidence: 99%

Design of interacting multi-stable nucleic acids for molecular information processing

Ramlan

Zauner

2011

Biosystems

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Abstract. Despite an exponential increase in computing power over the past decades, present information technology falls far short of expectations in areas such as cognitive systems and micro robotics. Organisms demonstrate that it is possible to implement information processing in a radically different way from what we have available in present technology, and that there are clear advantages from the perspective of power consumption, integration density, and real-time processing of ambiguous data. Accordingly, the question whether the current silicon substrate and associated computing paradigm is the most suitable approach to all types of computation has come to the fore. Macromolecular materials, so successfully employed by nature, possess uniquely promising properties as an alternate substrate for information processing. The two key features of macromolecules are their conformational dynamics and their self-assembly capabilities. The purposeful design of macromolecules capable of exploiting these features has proven to be a challenge, however, for some groups of molecules it is increasingly practicable. We here introduce an algorithm capable of designing groups self-assembling of nucleic acid molecules with multiple conformational states. Evaluation using natural and artificially designed nucleic acid molecules favours this algorithm significantly, as compared to the probabilistic approach. Furthermore, the thermodynamic properties of the generated candidates are within the same approximation as the customised trans-acting switching molecules reported in the laboratory.

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“…in an unpaired region. To predict possible binding sites it is therefore of interest to compute the probability P 0 [i, j] that a sequence interval [i, j] is unpaired, as is done in the RNAup program [17]. However, since RNAup folds the complete molecule, its CPU requirements scale as O(n 3 ), making it unsuitable for very long sequences.…”

Section: A Scanning Version Of Rnaupmentioning

confidence: 99%

Variations on RNA folding and alignment: lessons from Benasque

et al. 2007

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Dynamic Programming Algorithms solve many standard problems of RNA bioinformatics in polynomial time. In this contribution we discuss a series of variations on these standard methods that implement refined biophysical models, such as a restriction of RNA folding to canonical structures, and an extension of structural alignments to an explicit scoring of stacking propensities. Furthermore, we demonstrate that a local structural alignment can be employed for ncRNA gene finding. In this context we discuss scanning variants for folding and alignment algorithms.

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Thermodynamics of RNA–RNA binding

Abstract: RNAup will be distributed as part of the Vienna RNA Package, www.tbi.univie.ac.at/~ivo/RNA/

Cited by 339 publications

References 45 publications

Fast Prediction of RNA-RNA Interaction

Fast Prediction of RNA-RNA Interaction

Design of interacting multi-stable nucleic acids for molecular information processing

Variations on RNA folding and alignment: lessons from Benasque

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