Pfold: RNA secondary structure prediction using stochastic context-free grammars

By Bjarne Knudsen, Jotun Hein. Nucleic Acids Res., 2003

511 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/fe2f384611cc5c83f4845398cafe724aea24f76e

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Citations in the corpus

Improved accuracy of multiple ncRNA alignment by incorporating structural information into a MAFFT-based framework (2008, methodology): “multiple sequence alignment, they require, like plan A, an external program to predict a common secondary structure, such as RNAalifold [31], McCaskill-MEA [32] and Pfold [33].”
A comprehensive comparison of comparative RNA structure prediction approaches (2004, methodology): “Pfold implements a "stochastic context free grammar" (SCFG) designed to produce a "prior probability distribution of RNA structures" for an RNA alignment input [23,24,77].”
Identification and Classification of Conserved RNA Secondary Structures in the Human Genome (2006, unknown): “stochastic context-free grammar (phylo-SCFG) [10,16,17],”
Gen: a general-purpose probabilistic programming system with programmable inference (2019, methodology): “Recurse is used to implement recursive computation patterns including probabilistic context free grammars, which are a common building block of probabilistic models [17, 25, 33].”
Evaluation of several lightweight stochastic context-free grammars for RNA secondary structure prediction (2004, methodology): “G6 is the Knudsen/Hein grammar utilized in the Pfold package [18, 26 ].”
A benchmark of multiple sequence alignment programs upon structural RNAs (2005, unknown): “Structural 0.9789 1.0000 0 0.9297 1.0000 0 0.7846 1.0000 0 Align-m (1) 0.9827 0.9600 5 0.8453 0.8825 22 0.4957 0.6748 25 Align-m (2) 0.9827 0.9600 6 0.8453 0.8825 21 0.4957 0.6748 24 Align-m (3) 0.9778 0.9593 7 0.8040 0.8742 26 0.4691 0.6635 29 Align-m ( 4 ) 0.9778 0.9593 8 0.8040 0.8742 25 0.4691 0”
IPknot: fast and accurate prediction of RNA secondary structures with pseudoknots using integer programming (2011, methodology): “We can regard this approach as maximizing expected accuracy, which has been successfully applied into various problems (Carvalho and Lawrence, 2008; Do et al, 2005; Do et al., 2006, 2008; Hamada et al., 2009a, b, 2010, 2011; Kato et al., 2010; Knudsen and Hein, 2003).”
Knowledge-based machine learning methods for macromolecular 3D structure prediction (2016, background): “The base pairing states can be predicted using some secondary structure prediction programs (Akutsu, 2000; Do et al., 2006; Eddy and Durbin, 1994; Gardner and Giegerich, 2004; Knudsen and Hein, 2003; Mathews and Turner, 2006; Poolsap et al., 2009; Zuker, 2003) with reasonable accuracy.”
ViennaRNA Package 2.0 (2011, methodology): “When base pair probabilities are computed, the maximum expected accuracy (MEA) structure [18,72] is also available.”
A fast structural multiple alignment method for long RNA sequences (2008, methodology): “For two RNA sequences, x, y and k, l ∈ {1, ···, |x|}, m, n ∈ {1, ···, |y|}, let P(xk ~ ym, xl ~ yn, xk xl, ym yn|x, y) be the posterior probability, i.e. the sum of the probabilities that two positions of the sequences, xk and ym, xl and yn, are aligned in the alignment, and that two pairs of the nu”
Recent developments in the MAFFT multiple sequence alignment program (2008, methodology): “The SPS SCI values were computed for each alignment and then averaged across all the alignments.The alignment by each method was subjected to three external prediction programs, Pfold [ 112 ], McCaskill-MEA [90] and RNAalifold [89], and then the differences from the Rfam curated structure were calcu”
CONTRAfold: RNA secondary structure prediction without physics-based models (2006, methodology): “When g 1⁄4 1, the algorithm maximizes the expected number of correct positions and is identical to the parsing technique used in Pfold [9].”
CentroidFold: a web server for RNA secondary structure prediction (2009, background): “However, several studies have pointed out a drawback of the MFE/ML estimators that the MFE/ML structure generally has an extremely low probability and is even not optimal with respect to the number of corrected predicted base pairs (5–8).”