ArticleBMC bioinformatics2013
Characterising RNA secondary structure space using information entropy.
Article in BMC bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Plastid Transformation of Micro-Tom Tomato with a Hemipteran Double-Stranded RNA Results in RNA Interference in Multiple Insect Species.International journal of molecular sciences · 2022Article
- On an enhancement of RNA probing data using information theory.Algorithms for molecular biology : AMB · 2020Article
- RNA Interference in the Tobacco Hornworm,Frontiers in plant science · 2019Article
- Characterization and visualization of RNA secondary structure Boltzmann ensemble via information theory.BMC bioinformatics · 2018Article
- Secondary structural entropy in RNA switch (Riboswitch) identification.BMC bioinformatics · 2015Article
- RNA Thermodynamic Structural Entropy.PloS one · 2015Article
- Quantifying variances in comparative RNA secondary structure prediction.BMC bioinformatics · 2013Article
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Authors and funding
6 authors.
Funding
Abstract
Comparative methods for RNA secondary structure prediction use evolutionary information from RNA alignments to increase prediction accuracy. The model is often described in terms of stochastic context-free grammars (SCFGs), which generate a probability distribution over secondary structures. It is, however, unclear how this probability distribution changes as a function of the input alignment. As prediction programs typically only return a single secondary structure, better characterisation of the underlying probability space of RNA secondary structures is of great interest. In this work, we show how to efficiently compute the information entropy of the probability distribution over RNA secondary structures produced for RNA alignments by a phylo-SCFG, and implement it for the PPfold model. We also discuss interpretations and applications of this quantity, including how it can clarify reasons for low prediction reliability scores. PPfold and its source code are available from http://birc.au.dk/software/ppfold/.
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