A statistical sampling algorithm for RNA secondary structure prediction.

By Ye Ding, Charles E. Lawrence. Nucleic Acids Research, 2003

600 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/79699317487557f3d4d6eb53b69d972e4437a444

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Citations in the corpus

RNAstructure: software for RNA secondary structure prediction and analysis (2010, background): “Alternatively, structures can be sampled from the Boltzmann ensemble and a centroid, i.e. representative structure, determined [16,17].”
RNA secondary structure prediction by centroids in a Boltzmann weighted ensemble. (2005, methodology): “These two methods focus on the lowest end of the free energy density of states, whereas structure sampling allows characterization of Boltzmann-weighted density of states (Ding and Lawrence 2003).”
Thermodynamics of RNA-RNA Binding (2006, methodology): “The approach presented here therefore overcomes inherent limitations in sampling approaches such as Sfold [6, 5].”
Thermodynamic Analysis of Interacting Nucleic Acid Strands (2007, methodology): “These tools are useful in practice for the analysis and design of functional nucleic acid systems [8, 22, 12, 29, 28].”
Evaluation of several lightweight stochastic context-free grammars for RNA secondary structure prediction (2004, methodology): “Suboptimal parse trees can be sampled from their posterior probability distribution by a probabilistic traceback of the Inside matrix, analogous to techniques used for energy minimization algorithms [10,22,42].”
CentroidFold: a web server for RNA secondary structure prediction (2009, methodology): “These include the centroid estimator employed by Sfold (6,7) and the maximum expected accuracy (MEA) estimator employed by CONTRAfold (9).”
Using an RNA secondary structure partition function to determine confidence in base pairs predicted by free energy minimization. (2004, methodology): “This has been implemented in a partition function that includes pseudoknots (Dirks and Pierce 2003), but was not implemented for this algorithm, so that the same energy function as the MFE structure prediction algorithm (Mathews et al. 2004) is used.”
A structural analysis of in vitro catalytic activities of hammerhead ribozymes (2007, neutral): “In recent years, an alternative sampling approach to RNA secondary structure prediction has been developed [ 32 ] and has been implemented as the Sfold program [33].”
A comprehensive comparison of comparative RNA structure prediction approaches (2004, methodology): “We favoured recent algorithms which could be compiled on modern computers and those with input and output which could be simply dealt with (for example returning dot-bracket [13,37,91] or tabular-connect type formats [12,29,41], rather than coordinates and lengths of stacks or graphic (gif/pdf) repr”
ViennaRNA Package 2.0 (2011, methodology): “Ye Ding ’ s Sfold program [23] was the first to introduce stochastic structure sampling.”
Sfold web server for statistical folding and rational design of nucleic acids (2004, methodology): “Based on the RNA structure-sampling algorithm, we also developed a probability profiling method for the prediction of target accessibility (5,13).”
RNAstructure: web servers for RNA secondary structure prediction and analysis (2013, methodology): “Several methods are available for predicting structures for a single sequence, including maximum expected accuracy (25), stochastic sampling (26), exhaustive traceback (27) and pseudoknot prediction (28).”